Unified association centralized monitoring data management system for multiple traffic electromechanical devices
By constructing a traffic road topology map and dynamically dividing blocks, the status of vehicle lights can be identified, solving the problem that existing road lighting systems cannot accurately determine lighting needs, and realizing intelligent energy management and adaptive lighting control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHONGTIAN TECH (QINGYUAN) CO LTD
- Filing Date
- 2026-03-20
- Publication Date
- 2026-04-21
AI Technical Summary
Existing road lighting systems cannot accurately determine lighting needs, leading to energy waste or insufficiency, are unable to adapt to irregular weather changes, and lack in-depth analysis of the spatiotemporal distribution characteristics of traffic flow.
A traffic road topology map is constructed, monitoring blocks are dynamically divided, vehicle image data is acquired through high-definition cameras and GPS locators, vehicle light status and brightness are identified, differential analysis is performed, and lighting control commands are generated.
Accurately assess road lighting needs, reduce energy waste, improve the intelligent management level of lighting systems, and adapt to complex road environments.
Smart Images
Figure CN121908435A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data management, specifically a unified, centralized monitoring and management system for multiple transportation electromechanical equipment. Background Technology
[0002] With the acceleration of urbanization and the continuous growth of motor vehicle ownership, road traffic systems are becoming increasingly complex, and the demand for intelligent management is becoming more and more urgent. Modern roads are equipped with a large number of traffic electromechanical devices. In the field of road lighting control, road lighting systems typically employ timed control or automatic control based on ambient light sensors. Traditional lighting control mainly relies on timed control or ambient light sensors. Timed control cannot adapt to irregular scenarios such as sudden weather changes; ambient light sensors can only sense the overall light intensity and cannot distinguish whether insufficient light truly affects driving safety. Furthermore, if the ambient light gradually dims, but there are few vehicles on the road, turning on the lights too early will result in energy waste. Some intelligent lighting systems attempt to introduce traffic flow detection, using the number of vehicles to determine whether to turn on the lights. However, this approach has serious flaws. It cannot detect the on / off status of vehicle lights to help determine the demand for road lighting. Furthermore, it lacks in-depth analysis of the spatiotemporal distribution characteristics of traffic flow. The demand for road lighting depends not only on the current traffic flow but also on factors such as the changing trends of traffic flow, the continuity of road segments before and after, and the mutual influence of opposing lanes.
[0003] This application aims to pre-connect to a traffic monitoring system, acquire real-time traffic monitoring system data to construct a target road topology map, determine the current traffic direction attribute of the monitored road, dynamically divide the target road into multiple locations and blocks, dynamically identify single monitoring areas of the target road at different fixed time stamps for refined image analysis, screen the on / off status of vehicle body lights within the blocks and quantify the brightness detection, accurately distinguish between regular daytime running lights and actual lighting lights, perform differential correlation analysis between single-lane and two-lane traffic lights on the target road based on the road traffic direction attribute, determine the continuity and growth trend of traffic lighting demand on the target road, and comprehensively assess the overall lighting demand of traffic flow on the target road. Summary of the Invention
[0004] The purpose of this invention is to provide a unified, centralized monitoring and management system for multiple transportation electromechanical equipment to solve the problems in the prior art.
[0005] To achieve the above objectives, the present invention provides the following technical solution: A unified and centralized monitoring and management system for multiple traffic electromechanical devices, comprising a traffic road topology construction vehicle data access module, a multi-road dynamic area division monitoring and marking module, a road vehicle single-block light status monitoring and screening module, a multi-block vehicle light activation correlation analysis module, a background lighting system remote control decision module, and an equipment sharing and linkage platform; The traffic road topology construction vehicle data access module is pre-connected to the front-end monitoring equipment of the target traffic road. Based on the spatial geographic information of the target traffic road, the traffic direction attribute of the road is determined, and a directed road graph with different traffic direction attributes is constructed. The multi-road dynamic area division monitoring and marking module divides the target traffic road into multiple locations and blocks. It divides the target traffic road into multiple continuous monitoring blocks according to the traffic direction attribute, and counts the number of vehicles in each monitoring block in real time to effectively screen and determine the single monitoring block. The road vehicle single-block lighting status monitoring and screening module dynamically captures vehicle boundary boxes for a single monitoring block, performs brightness quantification analysis on the lighting area of the vehicle boundary box, accurately identifies and removes vehicles that only turn on daytime running lights, and counts the number of vehicles with actual lighting lights on within the block. The multi-block vehicle light activation correlation analysis module performs differentiated weight correlation analysis on the vehicle light activation data of a single monitoring block within a one-way road and a two-way road for roads with different traffic direction attributes, and performs trend analysis and dynamic judgment on the light activation status of the target road. The remote control decision module of the background lighting system obtains the fixed-point timestamp that triggers the traffic lights to turn on in real time, and generates control commands to control the dynamic switching of traffic lights on the current road segment.
[0006] Further configuration: The traffic road topology construction vehicle data access module includes a front-end monitoring equipment access and acquisition submodule and a road spatial topology association and marking submodule. The front-end monitoring equipment access and acquisition submodule includes a multi-source traffic monitoring equipment connection input unit and a real-time road traffic data acquisition unit. The multi-source traffic monitoring equipment connection input unit includes access to several high-definition network cameras, road checkpoint cameras and GPS locators, and performs network adaptation access according to different monitoring equipment types. The real-time road traffic data acquisition unit collects vehicle image data and video data of the target road in real time from different monitoring equipment, and generates original image and video data of the target road vehicles including timestamps, acquisition monitoring equipment IDs and acquisition geographical locations. It performs preliminary cleaning of the original image and video data of the target road vehicles, and filters out vehicle original image and video data with clarity below a set threshold. The road spatial topology association and labeling submodule acquires the electronic map data of the target road, extracts the road spatial data of the target road, including the number of lanes, lane width, and road traffic direction, and determines the traffic direction attribute of the target road. If the electronic map data shows that the target road is a one-way traffic lane, it acquires the original image and video data of vehicles on the current target road. If the current target road only has single-lane vehicle trajectories, it determines that the target road has a one-way traffic direction attribute. If the electronic map data shows that the target road is a two-way traffic lane, it acquires the original image and video data of vehicles on the current target road. If the current target road has two-way vehicle trajectories, it determines that the target road has a two-way traffic direction attribute. Based on the traffic direction attribute of the target road, the continuous target roads are constructed into a directed graph network.
[0007] Further configuration: The multi-road dynamic area division monitoring and marking module includes a road multi-image time-series sampling submodule and a road dynamic block vehicle threshold comparison submodule. The road multi-image time-series sampling submodule acquires real-time raw image and video data streams of vehicles on the target road, sorts and classifies the real-time raw image and video data streams according to consecutive timestamps within the same date, and constructs a vehicle raw image and video data sequence indexed by time. Through the device sharing and linkage platform backend, several fixed-point timestamps within the same date that meet the sampling requirements are selected, and the time interval between two adjacent fixed-point timestamps is defined. Greater than the preset time threshold The set of fixed-point timestamps selected on the same date is , ; Obtain a set of selected fixed-point timestamps for different dates. For each selected fixed-point timestamp, randomly select images with a resolution greater than a set threshold from the original image / video data stream of the target road corresponding to that selected fixed-point timestamp. The image or video screenshot is used as a sample set for the current fixed-point timestamp. ,in The internal sampling samples of an image or video screenshot include one frame each from different angles of the target road; Further settings: The road dynamic block vehicle threshold comparison submodule, for a selected fixed-point timestamp sampling sample set, uses coordinate mapping to... The sampled image samples are fused and correlated, and unified into the planar coordinate system of the target road at the current fixed time stamp. The traffic direction attribute of the target road is obtained. According to the starting order of the traffic direction of the target road, the target road at the current fixed time stamp is divided into several continuous detection blocks. If the target road is a single lane, several detection blocks are divided only for the single lane traffic direction. If the target road is a two-lane road, several detection blocks are divided sequentially for the two lanes with different traffic directions. The target road is divided along the traffic direction. A continuous detection block, denoted as in, The starting block along the direction of travel for the target road. For the target road, the location information of each detection block along the direction of traffic is recorded. For the starting block Internal vehicle targets are detected to determine the starting block. Number of vehicles inside The administrator can preset the vehicle threshold for monitoring blocks. ,like Determine the current starting block The vehicle density conditions have been met; the starting block will be [transferred / removed / removed]. Mark the current fixed-point timestamp as a single monitoring block, and start the block. Assign a unique block ID to the current starting block. The block ID, timestamp, and number of vehicles are uploaded to the device sharing and linkage platform for the next adjacent block. Perform individual analyses sequentially; like Determine the current starting block If the vehicle density condition is not met, obtain the current starting block. The next adjacent block along the direction of travel , start block and the next adjacent block along the direction of travel Merge to form a merged block. Determine the merged blocks Number of vehicles inside ,like Determine the current merged block The conditions for high vehicle density have been met, and the blocks will be merged. Marked as a single monitoring block under the current fixed timestamp, and merged blocks Assigning a unique block ID will merge the blocks. The block ID, timestamp, and number of vehicles are uploaded to the device sharing and linkage platform. sequentially for the current starting block and detection blocks The next adjacent block along the direction of travel Perform merged analysis until a single monitoring block is formed for data uploading; The system iterates through all detection blocks within the target road along the traffic direction, summarizes the data of all single monitoring blocks of the target road at the current fixed timestamp, and also performs statistics on the data of all single monitoring blocks of the target road at several fixed timestamps on the same date.
[0008] Further configuration: The road vehicle single-block lighting status monitoring and screening module includes a multi-light area on-state screening sub-module and a vehicle lighting brightness quantification detection and recognition sub-module. The multi-light area on-state screening sub-module acquires data of all single monitoring blocks under several fixed-point timestamps on the target road on the current date, identifies and captures the vehicle bounding boxes of vehicles within each single monitoring block, extracts the image region of each vehicle bounding box for image enhancement and grayscale processing, and marks the areas with grayscale values greater than a set threshold within the image region of each vehicle bounding box as bright areas. If the proportion of bright areas within the image region of each vehicle bounding box is greater than a set judgment threshold, it is determined that the vehicle within the vehicle bounding box is in the on-light state, and the vehicle bounding box is screened and marked. Further settings: The vehicle headlight brightness quantization detection and recognition submodule obtains the number of bright areas within the image region of each vehicle bounding box, defines several bright areas within the image region of each vehicle bounding box as independent emitting areas of the vehicle light source, and sets several bright areas within the image region of each vehicle bounding box as follows: ,in, To determine the number of highlighted areas within each vehicle bounding box image region, a random vehicle bounding box is extracted from a single monitoring block at the current fixed timestamp. The average grayscale value of pixels within several highlighted areas of the vehicle bounding box image region is collected and defined as the comprehensive brightness of the vehicle light source within the vehicle bounding box. The average grayscale value of pixels within several highlighted areas is set to... The total number of pixels in several highlighted areas within the vehicle's bounding box image region is set to... , Calculate the headlight brightness index of a vehicle within the bounding box of a random vehicle in a single monitoring block at the current fixed timestamp. According to the formula: The calculation yields the headlight brightness index of vehicles within the bounding box of each vehicle in a single monitoring block at the current fixed timestamp. When the headlight brightness index of vehicles within that bounding box... If the brightness index of the lights of vehicles within the vehicle's bounding box is greater than or equal to a set threshold, the vehicle is considered to have its lights on and is marked as a valid vehicle bounding box. If the value is less than a set threshold, determine if the vehicle within the vehicle's bounding box is only using regular daytime running lights. Remove the vehicle bounding boxes corresponding to vehicles determined to have regular daytime running lights. Count the number of valid vehicle bounding boxes within all single monitoring blocks under several fixed timestamps on the same date and upload them.
[0009] Further configuration: The multi-block vehicle light activation correlation analysis module includes a one-way road multi-dimensional weight correlation analysis submodule and a two-way road multi-dimensional weight correlation analysis submodule. The multi-block vehicle light activation correlation analysis module obtains the number of valid vehicle bounding boxes within all single monitoring block data at several fixed timestamps on the same date, defined as the number of vehicles actually turning on their lights within all single monitoring block data at several fixed timestamps. The one-way road multi-dimensional weight correlation analysis submodule obtains the traffic direction attribute of the target road. If the target road has a one-way traffic direction attribute, it iterates through the number of vehicles actually turning on their lights within all single monitoring block data at several fixed timestamps on the current date, and obtains the currently collected fixed timestamps. Get the fixed-point timestamp The number of vehicles with their lights actually on within the first single monitoring block in the direction of the target road starting below. The administrator of the device sharing and linkage platform pre-sets a threshold for determining the number of vehicles with their lights on in each individual monitoring block. The threshold is set as follows: ; When the fixed-point timestamp The number of vehicles with their lights actually on within the single monitoring area starting from the target road. Determine the current timestamp The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block along the target road; When the fixed-point timestamp The number of vehicles with their lights actually on within the single monitoring area starting from the target road. Select the current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp Get the number of vehicles with their lights actually on within a single block along the direction of travel on the target road within adjacent fixed-point timestamps, and set the current fixed-point timestamp. The adjacent previous fixed-point timestamp The number of vehicles with their lights actually on inside the single block starting from the direction of travel on the internal target road. Current fixed-point timestamp The next adjacent fixed-point timestamp The number of vehicles with their lights actually on inside the single block starting from the direction of travel on the internal target road. ,when ,and If the current fixed-point timestamp and the adjacent fixed-point timestamps both meet the triggering conditions for turning on the traffic lights, the current and adjacent fixed-point timestamps are sent to the device sharing and linkage platform as trigger markers. If it exists or If no adjacent fixed-point timestamp of the current fixed-point timestamp reaches the judgment threshold, then a continuous sequence including the current fixed-point timestamp is selected. A fixed-point timestamp, of which the number of selected timestamps is... Set by humans to obtain Calculate the number of vehicles with their lights actually on within a single block along the direction of traffic on the target road at consecutive fixed-point timestamps. The percentage of vehicles with lights actually on in a single monitoring block along the direction of traffic on the target road at consecutive fixed timestamps, and the percentage of vehicles within that single monitoring block, is denoted as follows: Analyze the trend slope of the proportion sequence. If the trend slope is upward, determine the fixed-point timestamp of the current time period. The number of vehicles with their lights actually on within the first single monitoring block in the direction of the target road starting below. ,like , , If the threshold is exceeded and is set manually, then the current fixed-point timestamp is determined to meet the triggering condition for turning on the traffic lights, and the current fixed-point timestamp is sent to the device sharing and linkage platform as a trigger marker. If the trend slope is not an upward trend or Then determine the current timestamp. The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block on the target road.
[0010] Further settings: The multi-dimensional weighted correlation analysis submodule for two-way roads obtains the traffic direction attribute of the target road. If the target road has a two-way traffic direction attribute, it iterates through the data of all single monitoring blocks under several fixed timestamps on the current date to obtain the number of vehicles with their lights actually on within each block, and obtains the fixed timestamp of the current real-time data collection. Get the fixed-point timestamp Within the target road, the initial single monitoring block along both directions of traffic is marked as the left-hand starting single monitoring block and the right-hand starting single monitoring block, and a fixed-point timestamp is obtained. The number of vehicles with their lights actually on within the single monitoring block starting from the left and the single monitoring block starting from the right along the target road in both directions of traffic. , ; When the fixed-point timestamp The number of vehicles with their lights actually on inside any single monitoring block starting from the left and the single monitoring block starting from the right on the target road. or Determine the current timestamp The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block along the target road; When the fixed-point timestamp The number of vehicles with their lights actually on inside both the single monitoring block starting from the left and the single monitoring block starting from the right on the target road below both meet the requirements. or Determine the current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp Get the current fixed-point timestamp respectively The adjacent previous fixed-point timestamp The number of vehicles with their interior lights actually on within the single monitoring block starting on the left and the single monitoring block starting on the right of the target road. , Get the current fixed-point timestamp respectively The next adjacent fixed-point timestamp The number of vehicles with their interior lights actually on within the single monitoring block starting on the left and the single monitoring block starting on the right of the target road. , The above current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp The number of vehicles with their lights actually on inside the single monitoring block starting from the left and the single monitoring block starting from the right on the target road is compared with a pre-set threshold for the number of vehicles with their lights on in each single monitoring block. If the threshold is met... , , , If it is determined that both the current fixed-point timestamp and the adjacent fixed-point timestamps within the target road meet the triggering conditions for turning on the traffic lights, the current and adjacent fixed-point timestamps are sent to the device sharing and linkage platform as trigger markers. If the conditions are not met, select the one containing the current fixed-point timestamp. Including continuous A fixed-point timestamp, of which the number of selected timestamps is... Set by humans to obtain Calculate the number of vehicles with their lights actually on within each single monitoring block starting from the left and right of the target road under consecutive fixed-point timestamps. The percentage of vehicles with lights actually on within the left-hand and right-hand starting single monitoring blocks of the target road under consecutive fixed-point timestamps, and the percentage of the total number of vehicles within the corresponding left-hand and right-hand starting single monitoring blocks. The sequence of vehicles with their lights actually on and the percentage of the total number of vehicles in a single monitoring block starting from the left on the target road at consecutive fixed timestamps is denoted as follows: ,analyze Trend slope of the sequence of the proportion of a single monitoring block starting from the left of the target road under consecutive fixed-point timestamps ,in The sequence of vehicles with their lights actually on and the corresponding percentage of the total number of vehicles in a single monitoring block starting from the right on the target road at consecutive fixed-point timestamps is denoted as follows: ,analyze Trend slope of the sequence of the proportion of a single monitoring block starting from the left of the target road under consecutive fixed-point timestamps ,like , All are showing an upward trend, determining the current fixed-point timestamp. Once the triggering conditions for turning on the traffic lights are met, the current fixed-point timestamp is sent as a trigger marker to the device sharing and linkage platform. when , If any trend is upward, collect the current time period's fixed-point timestamp. The number of vehicles with their lights actually on within the single monitoring block starting from the left and the single monitoring block starting from the right along the target road in both directions of traffic. , If satisfied ,and Determine the current fixed-point timestamp If the trigger conditions for turning on the traffic lights are met, the current fixed-point timestamp is sent as a trigger marker to the device sharing and linkage platform; otherwise, the current timestamp is checked. The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block on the target road.
[0011] Further settings: The remote control decision module of the background lighting system includes a lighting control command receiving submodule and a lighting activation safety verification submodule. The lighting control command receiving submodule obtains the fixed-point timestamps that trigger the daily traffic light activation in real time and sends them to the background for intelligent activation of traffic lights on the target road. The lighting activation safety verification submodule allows manual setting of the mandatory nighttime lighting activation time. If the time reaches the mandatory nighttime lighting activation time, the traffic light always-on mode is executed.
[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: it aims to pre-connect the traffic monitoring system to obtain real-time traffic monitoring system data to construct a target road topology map, determine the current traffic direction attribute of the monitored road, divide the target road into multiple dynamic blocks, dynamically identify the single monitoring area of the target road at different fixed time stamps for refined image analysis, screen the vehicle body light on status and quantify the brightness detection within the block, accurately distinguish between conventional daytime running lights and actual lighting, perform differential correlation analysis between single lane and two lanes of the target road based on the road traffic direction attribute, determine the continuity and growth trend of traffic lighting demand of the target road, and comprehensively assess the overall lighting demand of traffic flow on the target road. Attached Figure Description
[0013] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.
[0014] Figure 1 This is a schematic diagram of the real-time process structure of a unified and centralized monitoring data management system for multiple transportation electromechanical equipment according to the present invention; Figure 2 This is a module connection diagram of a unified, centralized monitoring and data management system for multiple transportation electromechanical equipment according to the present invention. Detailed Implementation
[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0016] Please see Figures 1-2In this embodiment of the invention, a unified and centralized monitoring data management system for multiple traffic electromechanical devices is provided. The system includes a traffic road topology construction vehicle data access module, a multi-road dynamic area division monitoring and marking module, a road vehicle single-block light status monitoring and screening module, a multi-block vehicle light activation correlation analysis module, a background lighting system remote control decision module, and an equipment sharing and linkage platform. The traffic road topology construction vehicle data access module, the multi-road dynamic area division monitoring and marking module, the road vehicle single-block light status monitoring and screening module, the multi-block vehicle light activation correlation analysis module, and the background lighting system remote control decision module are sequentially electrically connected and uniformly connected to the equipment sharing and linkage platform via a network. The traffic road topology construction vehicle data access module is pre-connected to the front-end monitoring equipment of the target traffic road. Based on the spatial geographic information of the target traffic road, the traffic direction attribute of the road is determined, and a directed road graph with different traffic direction attributes is constructed. It also includes the following technical solutions: the traffic road topology construction vehicle data access module includes a front-end monitoring equipment access and acquisition submodule and a road spatial topology association and marking submodule. The front-end monitoring equipment access and acquisition submodule includes a multi-source traffic monitoring equipment connection input unit and a road traffic data real-time acquisition unit. The multi-source traffic monitoring equipment connection input unit includes access to several road high-definition network cameras, road checkpoint cameras and GPS locators, and performs network adaptation access according to different monitoring equipment types. The road traffic data real-time acquisition unit uses vehicle image data and video data of the target road collected in real time by different monitoring equipment to generate original image and video data of the target road vehicles, including timestamps, acquisition monitoring equipment IDs and acquisition geographical locations. It also performs preliminary cleaning of the original image and video data of the target road vehicles, filtering out vehicle original image and video data with clarity below a set threshold. The road spatial topology association and labeling submodule acquires the electronic map data of the target road, extracts the road spatial data of the target road, including the number of lanes, lane width, and road traffic direction, and determines the traffic direction attribute of the target road. If the electronic map data shows that the target road is a one-way traffic lane, it acquires the original image and video data of vehicles on the current target road. If the current target road only has single-lane vehicle trajectories, it determines that the target road has a one-way traffic direction attribute. If the electronic map data shows that the target road is a two-way traffic lane, it acquires the original image and video data of vehicles on the current target road. If the current target road has two-way vehicle trajectories, it determines that the target road has a two-way traffic direction attribute. Based on the traffic direction attribute of the target road, the continuous target roads are constructed into a directed graph network.
[0017] The multi-road dynamic area division monitoring and marking module divides the target traffic road into multiple locations and blocks. It divides the target traffic road into multiple continuous monitoring blocks according to the traffic direction attribute, and counts the number of vehicles in each monitoring block in real time to effectively screen and determine the single monitoring block. It should be specifically explained that the multi-road dynamic area division monitoring and marking module includes a road multi-image time-series sampling submodule and a road dynamic block vehicle threshold comparison submodule. The road multi-image time-series sampling submodule acquires real-time raw image and video data streams of vehicles on the target road, sorts and classifies the real-time raw image and video data streams according to consecutive timestamps within the same date, and constructs a vehicle raw image and video data sequence indexed by time. Through the device sharing and linkage platform backend, several fixed-point timestamps within the same date that meet the sampling requirements are selected, and the time interval between two adjacent fixed-point timestamps is defined. Greater than the preset time threshold The set of fixed-point timestamps selected on the same date is , ; Obtain a set of selected fixed-point timestamps for different dates. For each selected fixed-point timestamp, randomly select images with a resolution greater than a set threshold from the original image / video data stream of the target road corresponding to that selected fixed-point timestamp. The image or video screenshot is used as a sample set for the current fixed-point timestamp. ,in The internal sampling samples of an image or video screenshot include one frame each from different angles of the target road; To further explain, the road dynamic block vehicle threshold comparison submodule, for a selected set of sampled samples at a fixed time stamp, uses coordinate mapping to... The sampled image samples are fused and correlated, and unified into the planar coordinate system of the target road at the current fixed time stamp. The traffic direction attribute of the target road is obtained. According to the starting order of the traffic direction of the target road, the target road at the current fixed time stamp is divided into several continuous detection blocks. If the target road is a single lane, several detection blocks are divided only for the single lane traffic direction. If the target road is a two-lane road, several detection blocks are divided sequentially for the two lanes with different traffic directions. The target road is divided along the traffic direction. A continuous detection block, denoted as in, The starting block along the direction of travel for the target road. For the target road, the location information of each detection block along the direction of traffic is recorded. For the starting block Internal vehicle targets are detected to determine the starting block. Number of vehicles inside The administrator can preset the vehicle threshold for monitoring blocks. ,like Determine the current starting block The vehicle density conditions have been met; the starting block will be [transferred / removed / removed]. Mark the current fixed-point timestamp as a single monitoring block, and start the block. Assign a unique block ID to the current starting block. The block ID, timestamp, and number of vehicles are uploaded to the device sharing and linkage platform for the next adjacent block. Perform individual analyses sequentially; like Determine the current starting block If the vehicle density condition is not met, obtain the current starting block. The next adjacent block along the direction of travel , start block and the next adjacent block along the direction of travel Merge to form a merged block. Determine the merged blocks Number of vehicles inside ,like Determine the current merged block The conditions for high vehicle density have been met, and the blocks will be merged. Marked as a single monitoring block under the current fixed timestamp, and merged blocks Assigning a unique block ID will merge the blocks. The block ID, timestamp, and number of vehicles are uploaded to the device sharing and linkage platform. sequentially for the current starting block and detection blocks The next adjacent block along the direction of travel Perform merged analysis until a single monitoring block is formed for data uploading; The system iterates through all detection blocks within the target road along the traffic direction, summarizes the data of all single monitoring blocks of the target road at the current fixed timestamp, and also performs statistics on the data of all single monitoring blocks of the target road at several fixed timestamps on the same date.
[0018] The road vehicle single-block lighting status monitoring and screening module dynamically captures vehicle boundary boxes for a single monitoring block, performs brightness quantification analysis on the lighting area of the vehicle boundary box, accurately identifies and removes vehicles that only turn on daytime running lights, and counts the number of vehicles with actual lighting lights on within the block. It should be specifically explained that the road vehicle single-block lighting status monitoring and screening module includes a multi-light area on-state screening sub-module and a vehicle lighting brightness quantification detection and recognition sub-module. The multi-light area on-state screening sub-module obtains data of all single monitoring blocks under several fixed timestamps on the target road on the same date, identifies and captures the vehicle bounding boxes of vehicles within each single monitoring block, extracts the image region of each vehicle bounding box for image enhancement and grayscale processing, and marks the areas with grayscale values greater than a set threshold within the image region of each vehicle bounding box as bright areas. If the proportion of bright areas within the image region of each vehicle bounding box is greater than a set judgment threshold, it is determined that the vehicle within the vehicle bounding box is in the on-light state, and the vehicle bounding box is screened and marked. Further explanation is needed: the vehicle headlight brightness quantization detection and recognition submodule obtains the number of bright areas within the image region of each vehicle bounding box, defines several bright areas within each vehicle bounding box image region as independent emitting areas of the vehicle's light source, and sets these bright areas within each vehicle bounding box image region as follows: ,in, To determine the number of highlighted areas within each vehicle bounding box image region, a random vehicle bounding box is extracted from a single monitoring block at the current fixed timestamp. The average grayscale value of pixels within several highlighted areas of the vehicle bounding box image region is collected and defined as the comprehensive brightness of the vehicle light source within the vehicle bounding box. The average grayscale value of pixels within several highlighted areas is set to... The total number of pixels in several highlighted areas within the vehicle's bounding box image region is set to... , Calculate the headlight brightness index of a vehicle within the bounding box of a random vehicle in a single monitoring block at the current fixed timestamp. According to the formula: The calculation yields the headlight brightness index of vehicles within the bounding box of each vehicle in a single monitoring block at the current fixed timestamp. When the headlight brightness index of vehicles within that bounding box... If the brightness index of the lights of vehicles within the vehicle's bounding box is greater than or equal to a set threshold, the vehicle is considered to have its lights on and is marked as a valid vehicle bounding box. If the value is less than a set threshold, determine if the vehicle within the vehicle's bounding box is only using regular daytime running lights. Remove the vehicle bounding boxes corresponding to vehicles determined to have regular daytime running lights. Count the number of valid vehicle bounding boxes within all single monitoring blocks under several fixed timestamps on the same date and upload them.
[0019] The multi-block vehicle light activation correlation analysis module performs differentiated weight correlation analysis on the vehicle light activation data of a single monitoring block within a one-way road and a two-way road for roads with different traffic direction attributes, and performs trend analysis and dynamic judgment on the light activation status of the target road. It needs to be specifically explained that the multi-block vehicle light activation correlation analysis module includes a one-way road multi-dimensional weight correlation analysis submodule and a two-way road multi-dimensional weight correlation analysis submodule. The multi-block vehicle light activation correlation analysis module obtains the number of valid vehicle bounding boxes within all single monitoring blocks of data under several fixed timestamps on the same date, defined as the number of vehicles actually turning on their lights within all single monitoring blocks of data under several fixed timestamps. The one-way road multi-dimensional weight correlation analysis submodule obtains the traffic direction attribute of the target road. If the target road has a one-way traffic direction attribute, it iterates through the number of vehicles actually turning on their lights within all single monitoring blocks of data under several fixed timestamps on the current date, and obtains the currently collected fixed timestamps. Get the fixed-point timestamp The number of vehicles with their lights actually on within the first single monitoring block in the direction of the target road starting below. The administrator of the device sharing and linkage platform pre-sets a threshold for determining the number of vehicles with their lights on in each individual monitoring block. The threshold is set as follows: ; When the fixed-point timestamp The number of vehicles with their lights actually on within the single monitoring area starting from the target road. Determine the current timestamp The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block along the target road; When the fixed-point timestamp The number of vehicles with their lights actually on within the single monitoring area starting from the target road. Select the current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp Get the number of vehicles with their lights actually on within a single block along the direction of travel on the target road within adjacent fixed-point timestamps, and set the current fixed-point timestamp. The adjacent previous fixed-point timestamp The number of vehicles with their lights actually on inside the single block starting from the direction of travel on the internal target road. Current fixed-point timestamp The next adjacent fixed-point timestamp The number of vehicles with their lights actually on inside the single block starting from the direction of travel on the internal target road. ,when ,and If the current fixed-point timestamp and the adjacent fixed-point timestamps both meet the triggering conditions for turning on the traffic lights, the current and adjacent fixed-point timestamps are sent to the device sharing and linkage platform as trigger markers. If it exists or If no adjacent fixed-point timestamp of the current fixed-point timestamp reaches the judgment threshold, then a continuous sequence including the current fixed-point timestamp is selected. A fixed-point timestamp, of which the number of selected timestamps is... Set by humans to obtain Calculate the number of vehicles with their lights actually on within a single block along the direction of traffic on the target road at consecutive fixed-point timestamps. The percentage of vehicles with lights actually on in a single monitoring block along the direction of traffic on the target road at consecutive fixed timestamps, and the percentage of vehicles within that single monitoring block, is denoted as follows: Analyze the trend slope of the proportion sequence. If the trend slope is upward, determine the fixed-point timestamp of the current time period. The number of vehicles with their lights actually on within the first single monitoring block in the direction of the target road starting below. ,like , , If the threshold is exceeded and is set manually, then the current fixed-point timestamp is determined to meet the triggering condition for turning on the traffic lights, and the current fixed-point timestamp is sent to the device sharing and linkage platform as a trigger marker. If the trend slope is not an upward trend or Then determine the current timestamp. The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block on the target road.
[0020] To further explain, the two-way road multi-dimensional weighted correlation analysis submodule obtains the traffic direction attribute of the target road. If the target road has a two-way traffic direction attribute, it iterates through the data of all single monitoring blocks under several fixed timestamps on the current date to obtain the number of vehicles with their lights actually on within each block, and obtains the currently collected fixed timestamp. Get the fixed-point timestamp Within the target road, the initial single monitoring block along both directions of traffic is marked as the left-hand starting single monitoring block and the right-hand starting single monitoring block, and a fixed-point timestamp is obtained. The number of vehicles with their lights actually on within the single monitoring block starting from the left and the single monitoring block starting from the right along the target road in both directions of traffic. , ; When the fixed-point timestamp The number of vehicles with their lights actually on inside any single monitoring block starting from the left and the single monitoring block starting from the right on the target road. or Determine the current timestamp The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block along the target road; When the fixed-point timestamp The number of vehicles with their lights actually on inside both the single monitoring block starting from the left and the single monitoring block starting from the right on the target road below both meet the requirements. or Determine the current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp Get the current fixed-point timestamp respectively The adjacent previous fixed-point timestamp The number of vehicles with their interior lights actually on within the single monitoring block starting on the left and the single monitoring block starting on the right of the target road. , Get the current fixed-point timestamp respectively The next adjacent fixed-point timestamp The number of vehicles with their interior lights actually on within the single monitoring block starting on the left and the single monitoring block starting on the right of the target road. , The above current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp The number of vehicles with their lights actually on inside the single monitoring block starting from the left and the single monitoring block starting from the right on the target road is compared with a pre-set threshold for the number of vehicles with their lights on in each single monitoring block. If the threshold is met... , , , If it is determined that both the current fixed-point timestamp and the adjacent fixed-point timestamps within the target road meet the triggering conditions for turning on the traffic lights, the current and adjacent fixed-point timestamps are sent to the device sharing and linkage platform as trigger markers. If the conditions are not met, select the one containing the current fixed-point timestamp. Including continuous A fixed-point timestamp, of which the number of selected timestamps is... Set by humans to obtain Calculate the number of vehicles with their lights actually on within each single monitoring block starting from the left and right of the target road under consecutive fixed-point timestamps. The percentage of vehicles with lights actually on within the left-hand and right-hand starting single monitoring blocks of the target road under consecutive fixed-point timestamps, and the percentage of the total number of vehicles within the corresponding left-hand and right-hand starting single monitoring blocks. The sequence of vehicles with their lights actually on and the percentage of the total number of vehicles in a single monitoring block starting from the left on the target road at consecutive fixed timestamps is denoted as follows: ,analyze Trend slope of the sequence of the proportion of a single monitoring block starting from the left of the target road under consecutive fixed-point timestamps ,in The sequence of vehicles with their lights actually on and the corresponding percentage of the total number of vehicles in a single monitoring block starting from the right on the target road at consecutive fixed-point timestamps is denoted as follows: ,analyze Trend slope of the sequence of the proportion of a single monitoring block starting from the left of the target road under consecutive fixed-point timestamps ,like , All are showing an upward trend, determining the current fixed-point timestamp. Once the triggering conditions for turning on the traffic lights are met, the current fixed-point timestamp is sent as a trigger marker to the device sharing and linkage platform. when , If any trend is upward, collect the current time period's fixed-point timestamp. The number of vehicles with their lights actually on within the single monitoring block starting from the left and the single monitoring block starting from the right along the target road in both directions of traffic. , If satisfied ,and Determine the current fixed-point timestamp If the trigger conditions for turning on the traffic lights are met, the current fixed-point timestamp is sent as a trigger marker to the device sharing and linkage platform; otherwise, the current timestamp is checked. The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block on the target road.
[0021] The remote control decision module of the background lighting system obtains the fixed-point timestamp that triggers the traffic lights to turn on in real time, and generates control commands to control the dynamic switching of traffic lights on the current road segment.
[0022] The remote control decision module of the background lighting system includes a lighting control instruction receiving submodule and a lighting turn-on safety verification submodule. The lighting control instruction receiving submodule obtains the fixed-point timestamps that trigger the daily traffic light turn-on and sends them to the background for intelligent target road traffic light turn-on. The lighting turn-on safety verification submodule manually sets the mandatory nighttime lighting turn-on time. If the time reaches the mandatory nighttime lighting turn-on time, the traffic light always-on mode is executed.
[0023] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.
Claims
1. A unified, centralized monitoring and management system for multiple transportation electromechanical equipment, characterized in that: The system includes a traffic road topology construction vehicle data access module, a multi-road dynamic area division monitoring and marking module, a road vehicle single-block light status monitoring and screening module, a multi-block vehicle light activation correlation analysis module, a background lighting system remote control decision module, and an equipment sharing and linkage platform. The traffic road topology construction vehicle data access module is pre-connected to the front-end monitoring equipment of the target traffic road. Based on the spatial geographic information of the target traffic road, the traffic direction attribute of the road is determined, and a directed road graph with different traffic direction attributes is constructed. The multi-road dynamic area division monitoring and marking module divides the target traffic road into multiple locations and blocks. It divides the target traffic road into multiple continuous monitoring blocks according to the traffic direction attribute, and counts the number of vehicles in each monitoring block in real time to effectively screen and determine the single monitoring block. The road vehicle single-block lighting status monitoring and screening module dynamically captures vehicle boundary boxes for a single monitoring block, performs brightness quantification analysis on the lighting area of the vehicle boundary box, accurately identifies and removes vehicles that only turn on daytime running lights, and counts the number of vehicles with actual lighting lights on within the block. The multi-block vehicle light activation correlation analysis module performs differentiated weight correlation analysis on the vehicle light activation data of a single monitoring block within a one-way road and a two-way road for roads with different traffic direction attributes, and performs trend analysis and dynamic judgment on the light activation status of the target road. The remote control decision module of the background lighting system obtains the fixed-point timestamp that triggers the traffic lights to turn on in real time, and generates control commands to control the dynamic switching of traffic lights on the current road segment.
2. The unified and centralized monitoring data management system for multiple transportation electromechanical equipment according to claim 1, characterized in that... The traffic road topology construction vehicle data access module includes a front-end monitoring equipment access and acquisition submodule and a road spatial topology association and marking submodule. The front-end monitoring equipment access and acquisition submodule includes a multi-source traffic monitoring equipment connection input unit and a real-time road traffic data acquisition unit. The multi-source traffic monitoring equipment connection input unit includes access to several high-definition network cameras, road checkpoint cameras and GPS locators, and performs network adaptation access according to different monitoring equipment types. The real-time road traffic data acquisition unit generates original image and video data of vehicles on the target road, including timestamps, acquisition monitoring equipment IDs and acquisition geographical locations, by real-time acquisition of vehicle image and video data of the target road through different monitoring equipment. The original image and video data of vehicles on the target road is preliminarily cleaned to filter out vehicle original image and video data with clarity below a set threshold. The road spatial topology association and labeling submodule acquires the electronic map data of the target road, extracts the road spatial data of the target road, including the number of lanes, lane width, and road traffic direction, and determines the traffic direction attribute of the target road. If the electronic map data shows that the target road is a one-way traffic lane, it acquires the original image and video data of vehicles on the current target road. If the current target road only has single-lane vehicle trajectories, it determines that the target road has a one-way traffic direction attribute. If the electronic map data shows that the target road is a two-way traffic lane, it acquires the original image and video data of vehicles on the current target road. If the current target road has two-way vehicle trajectories, it determines that the target road has a two-way traffic direction attribute. Based on the traffic direction attribute of the target road, the continuous target roads are constructed into a directed graph network.
3. The unified and centralized monitoring data management system for multiple transportation electromechanical equipment according to claim 1, characterized in that... The multi-road dynamic area division monitoring and marking module includes a road multi-image time-series sampling submodule and a road dynamic block vehicle threshold comparison submodule. The road multi-image time-series sampling submodule acquires real-time raw image and video data streams of vehicles on the target road, sorts and classifies the real-time raw image and video data streams according to consecutive timestamps within the same date, and constructs a vehicle raw image and video data sequence indexed by time. Through the device sharing and linkage platform backend, several fixed-point timestamps that meet the sampling requirements within the same date are selected, and the time interval between two adjacent fixed-point timestamps is defined. Greater than the preset time threshold The set of fixed-point timestamps selected on the same date is , ; Obtain a set of selected fixed-point timestamps for different dates. For each selected fixed-point timestamp, randomly select images with a resolution greater than a set threshold from the original image / video data stream of the target road corresponding to that selected fixed-point timestamp. The image or video screenshot is used as a sample set for the current fixed-point timestamp. ,in The internal sampling samples of an image or video screenshot include one frame each from different angles of the target road.
4. The unified and centralized monitoring data management system for multiple transportation electromechanical equipment according to claim 3, characterized in that... The road dynamic block vehicle threshold comparison submodule, for a selected set of sampled samples at a fixed time stamp, uses coordinate mapping to... The sampled image samples are fused and correlated, and unified into the planar coordinate system of the target road at the current fixed time stamp. The traffic direction attribute of the target road is obtained. According to the starting order of the traffic direction of the target road, the target road at the current fixed time stamp is divided into several continuous detection blocks. If the target road is a single lane, several detection blocks are divided only for the single lane traffic direction. If the target road is a two-lane road, several detection blocks are divided sequentially for the two lanes with different traffic directions. The target road is divided along the traffic direction. A continuous detection block, denoted as in, The starting block along the direction of travel for the target road. For the target road, the location information of each detection block along the direction of travel is recorded. For the starting block Internal vehicle targets are detected to determine the starting block. Number of vehicles inside The administrator can preset the vehicle threshold for monitoring blocks. ,like Determine the current starting block The vehicle density conditions have been met; the starting block will be [transferred / removed / removed]. Mark the current fixed-point timestamp as a single monitoring block, and start the block. Assign a unique block ID to the current starting block. The block ID, timestamp, and number of vehicles are uploaded to the device sharing and linkage platform for the next adjacent block. Perform individual analyses sequentially; like Determine the current starting block If the vehicle density condition is not met, obtain the current starting block. The next adjacent block along the direction of travel , start block and the next adjacent block along the direction of travel Merge to form a merged block. Determine the merged blocks Number of vehicles inside ,like Determine the current merged block The conditions for high vehicle density have been met, and the blocks will be merged. Marked as a single monitoring block under the current fixed timestamp, and merged blocks Assigning a unique block ID will merge the blocks. The block ID, timestamp, and number of vehicles are uploaded to the device sharing and linkage platform. sequentially for the current starting block and detection blocks The next adjacent block along the direction of travel Perform merged analysis until a single monitoring block is formed for data uploading; The system iterates through all detection blocks within the target road along the traffic direction, summarizes the data of all single monitoring blocks of the target road at the current fixed timestamp, and also performs statistics on the data of all single monitoring blocks of the target road at several fixed timestamps on the same date.
5. A unified, centralized monitoring and data management system for multiple transportation electromechanical equipment according to claim 1, characterized in that... The road vehicle single-block lighting status monitoring and screening module includes a multi-light area on-state preliminary screening submodule and a vehicle lighting brightness quantification detection and recognition submodule. The multi-light area on-state preliminary screening submodule acquires data of all single monitoring blocks on the target road at several fixed timestamps on the same date, identifies and captures the vehicle bounding boxes of vehicles within each single monitoring block, extracts the image region of each vehicle bounding box for image enhancement and grayscale processing, and marks the areas with grayscale values greater than a set threshold within the image region of each vehicle bounding box as bright areas. If the proportion of bright areas within the image region of each vehicle bounding box is greater than a set judgment threshold, it is determined that the vehicle within the vehicle bounding box is in the on-light state, and the vehicle bounding box is screened and marked.
6. A unified, centralized monitoring and data management system for multiple transportation electromechanical equipment according to claim 5, characterized in that... The vehicle headlight brightness quantization detection and recognition submodule obtains the number of bright areas within the image region of each vehicle bounding box, defines several bright areas within the image region of each vehicle bounding box as independent emitting areas of the vehicle light source, and sets several bright areas within the image region of each vehicle bounding box as follows: ,in, To determine the number of highlighted areas within each vehicle bounding box image region, a random vehicle bounding box is extracted from a single monitoring block at the current fixed timestamp. The average grayscale value of pixels within several highlighted areas of the vehicle bounding box image region is collected and defined as the comprehensive brightness of the vehicle light source within the vehicle bounding box. The average grayscale value of pixels within several highlighted areas is set to... The total number of pixels in several highlighted areas within the vehicle's bounding box image region is set to... , Calculate the headlight brightness index of a vehicle within the bounding box of a random vehicle in a single monitoring block at the current fixed timestamp. According to the formula: The headlight brightness index of vehicles within the bounding box of each vehicle in a single monitoring block at the current fixed timestamp is calculated. If the brightness index of the lights of vehicles within the vehicle's bounding box is greater than or equal to a set threshold, the vehicle is considered to have its lights on and is marked as a valid vehicle bounding box. If the value is less than a set threshold, determine if the vehicle within the vehicle's bounding box is only using regular daytime running lights. Remove the vehicle bounding boxes corresponding to vehicles determined to have regular daytime running lights. Count the number of valid vehicle bounding boxes within all single monitoring blocks under several fixed timestamps on the same date and upload them.
7. A unified, centralized monitoring and data management system for multiple transportation electromechanical equipment according to claim 1, characterized in that... The multi-block vehicle light activation correlation analysis module includes a one-way road multi-dimensional weight correlation analysis submodule and a two-way road multi-dimensional weight correlation analysis submodule. The multi-block vehicle light activation correlation analysis module obtains the number of valid vehicle bounding boxes within all single monitoring block data at several fixed timestamps on the same date, defined as the number of vehicles actually having their lights on within all single monitoring block data at several fixed timestamps. The one-way road multi-dimensional weight correlation analysis submodule obtains the traffic direction attribute of the target road. If the target road has a one-way traffic direction attribute, it iterates through the number of vehicles actually having their lights on within all single monitoring block data at several fixed timestamps on the current date to obtain the currently collected fixed timestamps. Get the fixed-point timestamp The number of vehicles with their lights actually on within the first single monitoring block in the starting direction of the target road. The administrator of the device sharing and linkage platform pre-sets a threshold for determining the number of vehicles with their lights on in each individual monitoring block. The threshold is set as follows: ; When the fixed-point timestamp The number of vehicles with their lights actually on within the single monitoring area starting from the target road. Determine the current timestamp The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block along the target road; When the fixed-point timestamp The number of vehicles with their lights actually on within the single monitoring area starting from the target road. Select the current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp Get the number of vehicles with their lights actually on within the starting single block of the target road along the traffic direction within adjacent fixed-point timestamps, and set the current fixed-point timestamp. The adjacent previous fixed-point timestamp The number of vehicles with their lights actually on inside the single block starting from the direction of travel on the internal target road. Current fixed-point timestamp The next adjacent fixed-point timestamp The number of vehicles with their lights actually on inside the single block starting from the direction of travel on the internal target road. ,when ,and If the current fixed-point timestamp and the adjacent fixed-point timestamps both meet the triggering conditions for turning on the traffic lights, the current and adjacent fixed-point timestamps are sent to the device sharing and linkage platform as trigger markers. If it exists or If no adjacent fixed-point timestamp of the current fixed-point timestamp reaches the judgment threshold, then a continuous sequence including the current fixed-point timestamp is selected. A fixed-point timestamp, of which the number of selected timestamps is... Set by humans to obtain Calculate the number of vehicles with lights actually turned on within a single block along the direction of traffic on the target road at consecutive fixed-point timestamps. The percentage of vehicles with lights actually on in a single monitoring block along the direction of traffic on the target road at consecutive fixed timestamps, and the percentage of vehicles within that single monitoring block, is denoted as follows: Analyze the trend slope of the proportion sequence. If the trend slope is upward, determine the fixed-point timestamp of the current time period. The number of vehicles with their lights actually on within the first single monitoring block in the starting direction of the target road. ,like , , If the threshold is exceeded and is set manually, then the current fixed-point timestamp is determined to meet the triggering condition for turning on the traffic lights, and the current fixed-point timestamp is sent to the device sharing and linkage platform as a trigger marker. If the trend slope is not an upward trend or Then determine the current timestamp. The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block on the target road.
8. A unified, centralized monitoring and data management system for multiple transportation electromechanical equipment according to claim 7, characterized in that... The bidirectional road multi-dimensional weighted correlation analysis submodule obtains the traffic direction attribute of the target road. If the target road has a bidirectional traffic direction attribute, it iterates through the data of all single monitoring blocks under several fixed timestamps on the current date to obtain the number of vehicles with lights actually turned on within each block, and obtains the currently collected fixed timestamp. Get the fixed-point timestamp Within the target road, the initial single monitoring block along both directions of traffic is marked as the left-hand starting single monitoring block and the right-hand starting single monitoring block, and a fixed-point timestamp is obtained. The number of vehicles with their lights actually on within the single monitoring block starting from the left and the single monitoring block starting from the right along the target road in both directions of traffic. , ; When the fixed-point timestamp The number of vehicles with their lights actually on inside any single monitoring block starting from the left and the single monitoring block starting from the right on the target road. or Determine the current timestamp The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block along the target road; When the fixed-point timestamp The number of vehicles with their lights actually on inside both the single monitoring block starting from the left and the single monitoring block starting from the right on the target road below both meet the requirements. or Determine the current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp Get the current fixed-point timestamp respectively The adjacent previous fixed-point timestamp The number of vehicles with their interior lights actually on within the single monitoring block starting on the left and the single monitoring block starting on the right of the target road. , Get the current fixed-point timestamp respectively The next adjacent fixed-point timestamp The number of vehicles with their interior lights actually on within the single monitoring block starting on the left and the single monitoring block starting on the right of the target road. , The above current fixed-point timestamp The adjacent previous fixed-point timestamp and the next fixed-point timestamp The number of vehicles with their lights actually on inside the single monitoring block starting from the left and the single monitoring block starting from the right on the target road is compared with a pre-set threshold for the number of vehicles with their lights on in each single monitoring block. If the threshold is met... , , , If it is determined that both the current fixed-point timestamp and the adjacent fixed-point timestamps within the target road meet the triggering conditions for turning on the traffic lights, the current and adjacent fixed-point timestamps are sent to the device sharing and linkage platform as trigger markers. If the conditions are not met, select the option that includes the current fixed-point timestamp. Including continuous A fixed-point timestamp, of which the number of selected timestamps is... Set by humans to obtain Calculate the number of vehicles with their lights actually on within each single monitoring block starting from the left and right of the target road under consecutive fixed-point timestamps. The percentage of vehicles with lights actually on within the left-hand and right-hand starting single monitoring blocks of the target road under consecutive fixed-point timestamps, and the percentage of the total number of vehicles within the corresponding left-hand and right-hand starting single monitoring blocks. The sequence of vehicles with their lights actually on and the percentage of the total number of vehicles in a single monitoring block starting from the left on the target road at consecutive fixed timestamps is denoted as follows: ,analyze Trend slope of the sequence of the proportion of a single monitoring block starting from the left of the target road under consecutive fixed-point timestamps ,in The sequence of vehicles with their lights actually on and the corresponding percentage of the total number of vehicles in a single monitoring block starting from the right on the target road at consecutive fixed-point timestamps is denoted as follows: ,analyze Trend slope of the sequence of the proportion of a single monitoring block starting from the left of the target road under consecutive fixed-point timestamps ,like , All are showing an upward trend, determining the current fixed-point timestamp. Once the triggering conditions for turning on the traffic lights are met, the current fixed-point timestamp is sent as a trigger marker to the device sharing and linkage platform. when , If any trend is upward, collect the current time period's fixed-point timestamp. The number of vehicles with their lights actually on within the single monitoring block starting from the left and the single monitoring block starting from the right along the target road in both directions of traffic. , If satisfied ,and Determine the current fixed-point timestamp If the trigger conditions for turning on the traffic lights are met, the current fixed-point timestamp is sent as a trigger marker to the device sharing and linkage platform; otherwise, the current timestamp is checked. The target road has not met the trigger conditions for traffic lights to turn on; continue checking the next specific timestamp. Data on the status of a single monitoring block on the target road.
9. A unified, centralized monitoring and data management system for multiple transportation electromechanical equipment according to claim 1, characterized in that... The background lighting system remote control decision module includes a lighting control command receiving submodule and a lighting activation safety verification submodule. The lighting control command receiving submodule obtains the fixed-point timestamps that trigger the daily traffic light activation in real time and sends them to the background for intelligent activation of traffic lights on the target road. The lighting activation safety verification submodule manually sets the mandatory nighttime lighting activation time. If the time reaches the mandatory nighttime lighting activation time, the traffic light always-on mode is executed.