Traffic signal lamp remote control system based on Internet of Things
By integrating multiple sensors and modules through the Internet of Things (IoT) system, multi-dimensional data acquisition and dynamic control of traffic lights have been achieved, solving the problems of insufficient data accuracy and fixed control modes in existing systems, and improving traffic management efficiency and safety.
Patent Information
- Application Number
- CN202511652545.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-12
- Publication Date
- 2026-02-17
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent transportation technology, specifically to a remote control system for traffic lights based on the Internet of Things. Background Technology
[0002] Faced with increasing urban traffic pressure, intelligent transportation systems (ITS) are currently the most effective way to solve traffic congestion. ITS are comprehensive traffic control platforms that effectively integrate information technology, data transmission technology, control technology, and computer technology. Traffic signal control within these systems plays the most direct and effective role in alleviating traffic congestion.
[0003] Existing remote traffic signal control systems suffer from limited data acquisition dimensions and insufficient accuracy. Most systems rely solely on a single monitoring device (such as a camera) to obtain vehicle information, making them highly susceptible to environmental factors such as visibility (fog, rain) and lighting conditions, leading to vehicle identification errors. Furthermore, they lack effective data collection on road conditions (temperature, water accumulation, icing) and regional weather conditions, resulting in a lack of comprehensive and reliable data support for subsequent control. Secondly, the control modes are rigid and lack coordination. Traditional systems often employ fixed signal timing schemes, failing to dynamically adjust according to real-time traffic flow. In cases of localized lane congestion, it is difficult to accurately allocate passage time for different lanes, easily triggering chain congestion. In the face of widespread congestion, there is a lack of efficient linkage mechanisms between regional processing equipment and remote central control equipment, resulting in delayed manual intervention and low traffic management efficiency. Therefore, it is necessary to propose a remote traffic signal control system based on the Internet of Things (IoT). Summary of the Invention
[0004] To address the problems in the existing technology, the present invention provides a traffic signal remote control system based on the Internet of Things.
[0005] The technical solution adopted by this invention to solve its technical problem is: a traffic signal light remote control system based on the Internet of Things, including a data collection module, a connection module, and a control module. The data collection module includes an area monitoring module, an area radar scanning module, a network data interaction module, a road data module, and a meteorological data collection module. The area monitoring module uses a traffic light intersection as a base point, and the area between the base point and the adjacent traffic lights is defined as an area, and monitors this area. The area radar scanning module uses millimeter-wave radar to scan vehicles near intersections in the area. The road data module is equipped with road surface condition sensors, which can detect road surface temperature, water depth, and icing conditions, thereby confirming vehicle driving conditions and speed. The meteorological data collection module is equipped with meteorological sensors that can detect the meteorological conditions of the road section, such as rainfall and visibility, thereby confirming the vehicle's driving conditions and speed. The control module includes a regional processing module and a remote data processing module. The area processing module sets up a front-end processing base station at the base point in the area, and processes the data aggregation of the area through the front-end processing base station, as well as the operation of equipment and the implementation of traffic light adjustments within the area. The remote data processing module is the central control terminal. Information processed by the regional processing modules is aggregated to the central control terminal. The central control terminal processes and summarizes the aggregated information, determines whether there are problems in adjacent areas after the regional processing modules have processed it, and controls the regional processing modules to perform secondary adjustment processing and central control coordination through the remote data processing module. The connection module is used for signal transmission, interaction, and electrical supply between the above modules.
[0006] Specifically, the connection module includes a signal base station connection module, a network connection module, and an electrical connection module; the signal base station connection module is used for information transmission between the area processing module and the area monitoring module, the area radar scanning module, the road data module, and the meteorological data collection module; the network connection module is used for information transmission between the remote data processing module and the network data interaction module and the area processing module; and the electrical connection module is used for the electrical supply of the above modules.
[0007] Specifically, the vehicle's speed under road and weather conditions, and the time required for the vehicle to pass through the intersection at the current speed, represent the time required for the current traffic efficiency.
[0008] Specifically, lanes within the area that extend towards the base point are uphill lanes, and lanes within the area that extend away from the base point are downhill lanes.
[0009] Specifically, the area monitoring module uses three sets of cameras, located at the base point of the area road segment and the middle of the uphill and downhill lanes, respectively. When visibility is clear, the area monitoring module identifies the number of vehicles in the uphill and downhill lanes, while the area radar scanning module assists the cameras in identifying the number of vehicles. When visibility is low, the area radar scanning module is mainly used to identify the number of vehicles queuing at intersections, while the area monitoring module assists the area radar scanning module.
[0010] Specifically, the network data interaction module collects vehicle destination and route data from the navigation platform, and can upload some data from the remote data processing module to issue congestion and early warning prompts through the navigation software to guide vehicles to detour in advance.
[0011] Specifically, if the meteorological sensor detects visibility <50m (foggy weather) or the road data module detects road surface icing (temperature <0℃ and water depth >2mm), an early warning is triggered, and the traffic light timing is adjusted synchronously (extending the green light transition interval by 2-3s to avoid sudden braking accidents).
[0012] Specifically, the millimeter-wave radar (detection distance 150-200m, accuracy ±0.5m) is arranged with one set of base points in each area, and the millimeter-wave radar scans once every 100ms to detect the length of vehicle queues on the main road.
[0013] An implementation of a traffic signal remote control system based on the Internet of Things includes the following steps: The first step is to collect road conditions in the current area through the road data module and vehicle driving conditions in the current area through the meteorological data collection module. The data is then transmitted to the base station in real time, and the base station calculates the current driving speed of the vehicle. The second step is to use the area monitoring module to collect data on vehicles on the roads in the current area, and use the area radar scanning module to scan vehicles and lead vehicles near the intersection, thereby supplementing the data from the area monitoring module and making it easier to confirm the accurate data of vehicles on the roads in the area. Third, when there is no congestion in either the uphill or downhill lanes, the traffic lights can be controlled to operate normally. The fourth step involves the base station detecting the number of vehicles at the intersection when congestion occurs within the area. 1) When the uphill lane is congested while the downhill lane is not congested, other uphill lanes in the area can be identified. When an uphill section with a small number of waiting vehicles is identified and the vehicles can pass through, the passage time of the traffic lights can be reduced based on the time required for the current vehicles to pass through the current traffic efficiency, and the time can be transferred to the traffic lights of the congested section to alleviate the congestion. 2) When the uphill lane is not congested but the downhill lane is congested, the number of vehicles in the congested downhill section can be determined by the area monitoring module and the area radar scanning module. The number of vehicles passing through each time can be determined, thereby determining the number of vehicles that can enter each time. Based on the time required for the efficiency of the number of vehicles that can enter, the time of the traffic lights can be reduced and the time can be transferred to the traffic lights of other sections to control the number of vehicles entering, avoid congestion in subsequent lanes, and facilitate the smooth flow of traffic in congested sections by reducing the time and transferring it to traffic lights in other directions. Fifth, when a complete traffic jam occurs, each base station uploads the data of the current area to the central control device, then counts the vehicle driving data on the navigation platform, and integrates the data through the central control device to determine the current congested road section and the road section to be congested by subsequent vehicle traffic. At this time, staff can operate the central control device and control the traffic lights through the central control device to carry out manual intervention, diversion, and traffic management operations.
[0014] The beneficial effects of this invention are as follows: The IoT-based remote traffic light control system described in this invention has multiple significant advantages: First, it provides accurate and comprehensive data acquisition. Through the collaborative work of regional monitoring and millimeter-wave radar, combined with road data modules, meteorological data collection modules, and network data interaction modules, it achieves the acquisition of vehicle, road condition, and weather information across all scenarios. It can identify vehicles in various scenarios, providing reliable data support for subsequent control. Second, it has outstanding intelligent dynamic control capabilities. The regional processing module and the remote data processing module work together. Under normal conditions, the regional processing module ensures the stable operation of the traffic lights, and during local congestion, it accurately adjusts the duration of lane traffic lights to alleviate congestion and avoid chain congestion. During total congestion, manual intervention through the central control device can complete traffic interception, diversion, and diversion operations, greatly improving traffic management efficiency. Third, it interacts with the central control device, using navigation software to issue congestion warnings and prompts to guide vehicles to detour in advance, effectively improving traffic safety and travel experience. Detailed Implementation
[0015] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.
[0016] This invention provides the following technical solutions: A traffic light remote control system based on the Internet of Things includes a data collection module, a connection module, and a control module. The data collection module includes an area monitoring module, an area radar scanning module, a network data interaction module, a road data module, and a meteorological data collection module. The area monitoring module uses a traffic light intersection as a base point, and the area between the base point and the adjacent traffic lights is defined as an area, which is then monitored. The area radar scanning module uses millimeter-wave radar to scan for vehicles near intersections in an area; The road data module is equipped with road surface condition sensors that can detect road surface temperature, water depth, and icing conditions, thereby confirming vehicle driving conditions and speed. The meteorological data collection module is equipped with meteorological sensors that can detect the meteorological conditions of the road section, such as rainfall and visibility, thereby determining the vehicle's driving conditions and speed. The control module includes a regional processing module and a remote data processing module. The area processing module sets up a front-end processing base station at the base point in the area, and processes the data aggregation of the area through the front-end processing base station, as well as the operation of equipment and the implementation and adjustment of traffic lights in the area. The remote data processing module is the central control terminal. Information processed by the regional processing modules is aggregated to the central control terminal. The central control terminal processes and summarizes the aggregated information, determines whether there are any problems in adjacent areas after the regional processing modules have processed it, and controls the regional processing modules to perform secondary adjustments and overall coordination through the remote data processing module. The connection module is used for signal transmission, interaction, and electrical supply between the above modules.
[0017] The connection module includes a signal base station connection module, a network connection module, and an electrical connection module. The signal base station connection module is used for information transmission between the area processing module and the area monitoring module, the area radar scanning module, the road data module, and the meteorological data collection module. The network connection module is used for information transmission between the remote data processing module and the network data interaction module and the area processing module. The electrical connection module is used for the electrical supply of the above modules.
[0018] Among them, the vehicle's speed under road conditions and weather conditions, and the time required for the vehicle to pass through the intersection at the current speed, are the time required for the current traffic efficiency.
[0019] Within the area, lanes heading towards the base point are designated as uphill lanes, while lanes heading away from the base point are designated as downhill lanes.
[0020] The area monitoring module uses three sets of cameras, located at the base point of the area road segment and the middle of the uphill and downhill lanes, respectively. When visibility is clear, the area monitoring module identifies the number of vehicles in the uphill and downhill lanes. The area radar scanning module assists the cameras in identifying the number of vehicles. When visibility is low, the area radar scanning module is mainly used to identify the number of vehicles queuing at intersections, while the area monitoring module assists the area radar scanning module.
[0021] The network data interaction module collects vehicle destination and route data from the navigation platform and can also upload some data from the remote data processing module to issue congestion warnings and alerts through the navigation software, guiding vehicles to take detours in advance.
[0022] Among them, when the meteorological sensor detects visibility <50m (foggy weather) or the road data module detects road surface icing (temperature <0℃ and water depth >2mm), an early warning is triggered, and the traffic light timing is adjusted simultaneously (extending the green light transition interval by 2-3s to avoid sudden braking accidents).
[0023] Among them, a set of millimeter-wave radars (detection distance 150-200m, accuracy ±0.5m) is set up at each area base point, and the millimeter-wave radars scan once every 100ms to detect the length of vehicle queues on the main road.
[0024] An implementation of a traffic signal remote control system based on the Internet of Things includes the following steps: The first step is to collect road conditions in the current area through the road data module and vehicle driving conditions in the current area through the meteorological data collection module. The data is then transmitted to the base station in real time, and the base station calculates the current driving speed of the vehicle. The second step is to use the area monitoring module to collect data on vehicles on the roads in the current area, and use the area radar scanning module to scan vehicles and lead vehicles near the intersection, thereby supplementing the data from the area monitoring module and making it easier to confirm the accurate data of vehicles on the roads in the area. Third, when there is no congestion in either the uphill or downhill lanes, the traffic lights can be controlled to operate normally. The fourth step involves the base station detecting the number of vehicles at the intersection when congestion occurs within the area. 1) When the uphill lane is congested while the downhill lane is not congested, other uphill lanes in the area can be identified. When an uphill section with a small number of waiting vehicles is identified and the vehicles can pass through, the passage time of the traffic lights can be reduced based on the time required for the current vehicles to pass through the current traffic efficiency, and the time can be transferred to the traffic lights of the congested section to alleviate the congestion. 2) When the uphill lane is not congested but the downhill lane is congested, the number of vehicles in the congested downhill section can be determined by the area monitoring module and the area radar scanning module. The number of vehicles passing through each time can be determined, thereby determining the number of vehicles that can enter each time. Based on the time required for the efficiency of the number of vehicles that can enter, the time of the traffic lights can be reduced and the time can be transferred to the traffic lights of other sections to control the number of vehicles entering, avoid congestion in subsequent lanes, and facilitate the smooth flow of traffic in congested sections by reducing the time and transferring it to traffic lights in other directions. Fifth, when a complete traffic jam occurs, each base station uploads the data of the current area to the central control device, then counts the vehicle driving data on the navigation platform, and integrates the data through the central control device to determine the current congested road section and the road section to be congested by subsequent vehicle traffic. At this time, staff can operate the central control device and control the traffic lights through the central control device to carry out manual intervention, diversion, and traffic management operations.
[0025] Example: 1. Normal operating conditions (sunny day, dry road surface, no congestion) Step 1: Data Acquisition and Preprocessing The road data module detected a road surface temperature of 25℃ and a water depth of 0mm, determining the road surface to be dry; the meteorological data module detected a visibility of 5km, determining the weather to be normal. The area monitoring module uses three sets of cameras to identify the number of vehicles in the uphill lane (15 vehicles) and downhill lane (12 vehicles) in area AB; the area radar scanning module scans simultaneously to confirm that the error in the number of vehicles is less than 1 vehicle and calculates the average vehicle speed as 50 km / h. The network data interaction module collects data from the navigation platform, showing that approximately 20 vehicles will be heading towards point A within the next 10 minutes, with no concentrated traffic flow.
[0026] Step 2: Timing Calculation and Execution The regional processing module calculates that it takes about 2.2 seconds for a vehicle to pass through the A base point intersection (30m wide) at 50km / h. Based on the number of vehicles in the lanes, the green light duration for the main road is determined to be 40 seconds, the green light duration for the secondary road is 25 seconds, and the green light transition interval is 1 second. The regional processing module controls the traffic lights at base point A to operate according to the above timing, and at the same time uploads the data to the remote data processing module for record-keeping.
[0027] Step 3: Navigation Data Interaction The remote data processing module uploads the "no congestion" status of base point A and its surrounding area to the navigation platform. The navigation software does not trigger detour prompts and guides vehicles to pass normally.
[0028] 2. Severe weather conditions (fog + icy roads) Step 1: Warning Trigger The meteorological data module detected a visibility of 45m (<50m), and the road data module detected a road surface temperature of -2℃ and a water depth of 3mm (meeting the conditions for icing), triggering a dual warning for "fog + icing". The regional processing module synchronously uploads the early warning information to the remote data processing module, which then issues a "Fog and icy road conditions ahead, slow down" warning through the navigation platform.
[0029] Step 2: Timing Adjustment The area processing module calculates that the vehicle's speed can be reduced to 20km / h, and the time required to pass through the intersection is approximately 5.4s; at the same time, according to the warning rules, the green light transition interval is extended to 3s (from 1s) to avoid sudden braking accidents. Adjusted timing: Green light duration for main roads is 50 seconds, green light duration for secondary roads is 35 seconds, and green light transition interval is 3 seconds; the area processing module controls the traffic lights to execute the new timing and displays "Fog and icy conditions, drive with caution" on the LED screen on the traffic light pole.
[0030] 3. Localized congestion (blockage in the uphill lanes of areas A and B) Step 1: Congestion Identification At 8:00 AM during the morning rush hour, the queue length of vehicles on the northbound lane (main road) in area AB reached 180m (detected by radar scanning module), and the vehicle speed dropped to 10km / h, which was determined to be "congestion on the northbound lane"; the queue length of vehicles on the southbound lane was 20m, with no congestion. The area monitoring module confirmed that the camera in the middle of the uphill lane showed vehicles queuing up to 350m, which is consistent with the radar data.
[0031] Step 2: Localized drainage The area processing module identifies that there are only 5 vehicles in the AC area's uphill lane (secondary arterial road), with few waiting vehicles and the road is passable; it calculates that the time required for vehicles in the AC area's uphill lane to pass through the intersection is about 3 seconds, which can reduce the green light time by 5 seconds. The area processing module reduces the green light duration of the uphill lane in the AC area from 25s to 20s, and adds the 5s reduction to the green light duration of the uphill lane in the AB area (increasing it from 40s to 45s). Within 10 minutes of the adjustment, the queue length of the uphill lanes in area AB was reduced to 80m, alleviating congestion.
[0032] 4. Overall traffic congestion (all three areas surrounding point A are congested) Step 1: Data Summary and Analysis During the morning rush hour at 8:30, vehicle queues exceeding 200m occurred in areas AB, AC, and AD. The area processing module uploaded data from each area (number of vehicles, driving speed, road / weather data) to the remote data processing module. The remote data processing module integrates navigation platform data and discovers that 80 vehicles plan to travel from point A to the city center within the next 15 minutes. If no intervention is taken, congestion will worsen.
[0033] Step 2: Manual intervention and overall coordination Traffic control center staff initiated a "traffic interception + diversion + traffic management" plan through the manual interface of the remote data processing module: Traffic diversion: Reduce the green light duration of the northbound lanes in areas AB and AC to 15 seconds to restrict vehicles from entering point A; Traffic management: Increase the green light duration for the downhill lanes in the AD area to 50 seconds to expedite vehicle departure from point A; Traffic diversion: The navigation platform will issue a prompt that “there is congestion around point A, it is recommended to take XX Road” to guide 30% of vehicles that plan to go to point A to change their routes.
[0034] Step 3: Congestion mitigation verification After 20 minutes of manual intervention, the queue length of vehicles in the area surrounding point A decreased to less than 100m, the average vehicle speed returned to 30km / h, and the congestion was relieved; the remote data processing module recorded the data of the intervention process for subsequent timing algorithm optimization.
[0035] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.
Claims
1. A traffic signal remote control system based on Internet of Things, comprising a data collection module, a connection module and a control module, characterized in that, the data collection module comprises a regional monitoring module, a regional radar scanning module, a network data interaction module, a road data module and a meteorological data collection module: the regional monitoring module takes a signal traffic light intersection as a base point, and takes the adjacent signal traffic lights as a region, and monitors the region; the regional radar scanning module is a millimeter wave radar that scans vehicles near the intersection in the region; the road data module is installed with a road surface state sensor, which can detect road surface temperature, water depth and icing conditions, thereby confirming vehicle driving conditions and speed; the meteorological data collection module is installed with a meteorological sensor, which can detect the meteorological conditions of the road section, such as rainfall and visibility, thereby confirming the vehicle driving conditions and speed; the control module comprises a regional processing module and a remote data total processing module: the regional processing module sets a front-end processing base station at the base point in the region, and processes the data collected by the front-end processing base station, and controls the operation of the equipment in the region and the adjustment of the signal lights; the remote data total processing module is a total control terminal, the information processed by the regional processing module is gathered to the total control terminal, the total control terminal processes and summarizes the gathered information, judges whether there is a problem in the adjacent region after the regional processing module processes, and controls the regional processing module to make secondary adjustment and processing and total control coordination through the remote data total processing module; the connection module is used for signal transmission, interaction and electrical supply between the above-mentioned modules.
2. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The connection module comprises a signal base station connection module, a network connection module and an electrical connection module; the signal base station connection module is used for information transmission between the regional processing module and the regional monitoring module, the regional radar scanning module, the road data module and the meteorological data collection module; the network connection module is used for information transmission between the remote data total processing module and the network data interaction module and the regional processing module; and the electrical connection module is used for electrical supply of the above-mentioned modules.
3. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The driving speed of the vehicle under the road state and meteorological conditions, and the time required for the vehicle to pass through the intersection at the current driving speed, is the time required for the current traffic efficiency.
4. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The lanes in the region that approach the base point are uplink lanes, and the lanes in the region that move away from the base point are downlink lanes.
5. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The regional monitoring module comprises three groups of cameras, which are respectively located at the base point of the regional road section, the middle segment of the uplink lane and the downlink lane. In the case of clear visibility, the number of vehicles on the uplink lane and the downlink lane is identified by the regional monitoring module, while the regional radar scanning module is used to assist the camera in identifying the number of vehicles, and in the case of low visibility, the regional radar scanning module is mainly used to identify the number of vehicles queuing at the intersection, while the regional monitoring module is used to assist the regional radar scanning module.
6. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The network data interaction module collects the vehicle driving destination and route data of the navigation platform, and uploads part of the data of the remote data total processing module, and issues congestion and early warning prompts through the navigation software to guide the vehicle to detour in advance.
7. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The weather sensor detects that the visibility is < 50m, or the road data module detects that the road surface is icy, triggering an early warning and synchronously adjusting the signal light timing.
8. The traffic signal remote control system based on the Internet of Things according to claim 1, characterized in that: The millimeter wave radar is arranged in groups at each regional base point, and the millimeter wave radar scans once every 100ms to detect the length of the vehicle queue on the main road. 9.A traffic signal lamp remote control method based on Internet of Things, the method is implemented by using the traffic signal lamp remote control system based on Internet of Things according to any one of claims 1-8, characterized in that, The method comprises the following steps: Firstly, the road data module collects the road state in the current area, and the weather data collection module collects the vehicle driving condition data in the current area, and then the data is transmitted to the base station in real time, and the current vehicle drivable speed is calculated by the base station; Secondly, the regional monitoring module counts the driving vehicle data on the current regional road, and the regional radar scanning module scans the driving vehicles near the intersection and the leading vehicles, and then supplements the data of the regional monitoring module to facilitate the confirmation of the accurate data of the vehicles on the road in the region; Thirdly, when there is no congestion on the uplink lane and the downlink lane, the traffic signal light can be controlled to operate normally; Fourthly, when congestion occurs in the region, the base station detects the number of vehicles at the intersection; 1) When the uplink lane is congested and the downlink lane is not congested, the other uplink lanes in the region can be identified, and when the current waiting vehicle quantity is small and the uplink section can complete vehicle passage, the passage time of the traffic signal light can be reduced according to the time required by the current vehicle based on the current passage efficiency, and the time can be converted to the traffic signal light of the congested section to dredge the congested section; 2) When the uplink lane is not congested and the downlink lane is congested, the number of vehicles on the congested downlink section can be determined by the regional monitoring module and the regional radar scanning module, and the number of vehicles that can enter each time can be determined, and the passage time of the traffic signal light can be reduced according to the time required by the number of vehicles that can enter based on the passage efficiency, and the time can be converted to the traffic signal light of other sections to control the number of entering vehicles, avoid congestion of subsequent lanes, and convert the time to the traffic signal light of other directions to facilitate auxiliary dredging of the congested section; Fifthly, when there is overall congestion, the base station uploads the data in the current region to the total control device, then the vehicle driving data on the navigation platform is counted, and the data is integrated by the total control device to determine the congested section and the congested section caused by the subsequent vehicle driving. At this time, the staff can operate the total control device and control the traffic signal light through the total control device to manually intervene in the traffic dredging operation.