IoT Traffic Light Timing Control via Pedestrian Data
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Solution Overview
Problem
Current traffic light management systems in smart cities lack efficiency in optimizing traffic flow, leading to congestion and reduced passing rates for vehicles and pedestrians, as they do not effectively adapt to real-time pedestrian and intersection data.
Innovation Solution
An Internet of Things (IoT) system comprising a user platform, service platform, management platform, sensor network platform, and object platform that collects and analyzes pedestrian and intersection information to dynamically adjust traffic light timing, using machine learning models for pedestrian recognition and prediction to determine optimal lighting durations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional fixed-time traffic light control is used, then the system is simple to operate, but traffic flow efficiency is reduced and congestion occurs
Solution Approach 1:
The traffic light control system transitions from fixed static timing to dynamic adaptive timing. The management platform receives real-time data from sensor networks (pedestrian detection, vehicle flow, weather conditions) and automatically adjusts traffic light durations based on current conditions, making the system flexible and responsive rather than rigid and predetermined
Solution Approach 2:
The system implements closed-loop feedback control by continuously monitoring traffic conditions through sensor networks and using this information to adjust traffic light timing. The management platform processes real-time data from multiple intersections and pedestrian detection devices, then sends control instructions back to traffic lights to optimize flow based on actual conditions rather than predetermined schedules
2Productivity
If real-time pedestrian and intersection data are collected and analyzed, then passing rate is improved, but system complexity increases
Solution Approach 1:
The management platform serves multiple functions: it collects data from sensor networks across multiple intersections, processes pedestrian detection information, analyzes traffic patterns, generates optimized timing schemes, and sends control instructions to traffic lights. This multi-functional centralized platform handles diverse tasks through a single system rather than requiring separate specialized systems for each function
Solution Approach 2:
The management platform acts as an intermediary between the sensor network platform (which collects raw data from traffic lights and pedestrian detection devices) and the object platform (which executes control instructions). It processes and translates raw sensor data into optimized timing schemes, then converts these schemes into control instructions for traffic light execution, mediating between data collection and action execution
3Productivity
If dynamic adjustment of traffic light timing is implemented, then congestion is reduced, but measurement and detection difficulty increases
Solution Approach 1:
The system divides the traffic monitoring and control function into separate specialized components: sensor networks for data collection, management platform for analysis and decision-making, and object platform for execution. This segmentation allows each component to focus on specific tasks, making the overall complex system manageable through modular functional division
Solution Approach 2:
The system implements self-service through automated pedestrian detection and timing optimization. Pedestrian detection devices automatically identify pedestrian presence and characteristics, the management platform automatically generates optimized timing schemes based on detected conditions, and traffic lights automatically adjust without manual intervention, making the system self-regulating rather than requiring constant human operation
Data Source
AI summary
The embodiment of the present disclosure provides a method for setting time of traffic lights in a smart city and an Internet of Things system. The method is implemented by an Internet of Things system for setting time of traffic lights in a smart city, which includes a user platform, a service platform, a management platform, a sensor network platform, and an object platform. The method includes: obtaining pedestrian information and intersection information of a target intersection, and the target intersection being an intersection provided with the traffic lights; determining, based on the pedestrian information and the intersection information, the scheme for setting time of the traffic lights at the target intersection; and sending a control instruction corresponding to the scheme for setting the time to the object platform, and in response to the received control instruction, controlling lighting duration of the traffic lights by the object platform.