IoT Tidal Lane Management Algorithm for Dynamic Traffic Control
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Solution Overview
Problem
Current urban traffic management systems fail to dynamically adjust tidal lane opening times, flow directions, and numbers in response to changing road traffic conditions, leading to inefficiencies in traffic flow.
Innovation Solution
An Internet of Things (IoT) system comprising a user platform, service platform, management platform, sensor network platform, and object platform that collects traffic data, determines optimal tidal lane management schemes using algorithms, and executes control instructions to adjust lane operations based on real-time traffic features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tidal lanes are set to alleviate traffic phenomenon, then traffic flow efficiency is improved, but the complexity of controlling opening time, flow direction, and number of tidal lanes increases
Solution Approach 1:
The system enables tidal lane control to automatically adjust opening times, flow directions, and lane numbers based on real-time traffic data collected from sensors and GPS devices. The algorithm autonomously processes traffic conditions and generates control instructions without manual intervention, allowing the system to self-regulate according to actual traffic patterns.
Solution Approach 2:
The system continuously monitors traffic conditions through sensor networks and GPS data, feeding this information back to the control algorithm. Based on this feedback loop, the system dynamically adjusts tidal lane configurations to optimize traffic flow, creating a closed-loop control system that adapts to changing traffic conditions.
2Adaptability or versatility
If tidal lane control is manually adjusted according to road traffic conditions, then adaptability to traffic changes is improved, but response time and operational efficiency deteriorate
Solution Approach 1:
The system replaces manual mechanical adjustment of tidal lane controls with an automated electronic control system. The algorithm processes traffic data and generates control instructions that are automatically transmitted to relevant devices, eliminating the time delay associated with manual observation and adjustment while maintaining adaptability to traffic conditions.
Solution Approach 2:
The system performs preliminary analysis of traffic patterns using historical data and real-time inputs to predict future traffic conditions. By anticipating traffic changes before they fully manifest, the system can proactively adjust tidal lane configurations in advance, reducing response time and preventing congestion rather than reacting to it.
Data Source
AI summary
A method for tidal lane opening management in a smart city is provided. The method applied to the management platform includes issuing a data obtaining instruction to a sensor network platform to obtain a first traffic feature of a target road within a first time period from an object platform, wherein the first traffic feature is a feature reflecting a flow situation of the target road, determining a target tidal lane opening scheme of the target road within the first time period based on the first traffic feature using a preset algorithm, generating a scheme execution instruction based on the target tidal lane opening program, sending the scheme execution instruction to the target object through, and issuing a data upload instruction to send the target tidal lane opening scheme to the user platform through a service platform.