Adaptive Multi-Region MFDs for Dynamic Traffic Congestion Mitigation
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Solution Overview
Problem
Current traffic congestion control methods using Macroscopic Fundamental Diagrams (MFDs) face challenges in managing large-scale traffic systems due to increasing metropolitan areas and dynamic road conditions, making it difficult to efficiently reduce congestion and improve traffic conditions.
Innovation Solution
A system that dynamically partitions a traffic network into smaller regions based on real-time traffic conditions, generates MFDs for each region, and adjusts routing algorithms to mitigate congestion by controlling vehicle inflows into congested areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional MFD-based traffic congestion control methods are used, then congestion mitigation is attempted, but the system becomes ineffective in large-scale metropolitan areas with dynamic road conditions
Solution Approach 1:
The patent divides the metropolitan traffic network into multiple smaller sub-regions, each with its own MFD. This segmentation allows the system to manage congestion locally in each sub-region while maintaining overall network-wide congestion mitigation, making the system more adaptable to dynamic conditions in large-scale metropolitan areas.
2Measurement precision
If the traffic network is divided into smaller partitions, then congestion control precision is improved, but system complexity increases
Solution Approach 1:
The traffic network is partitioned into multiple sub-regions, each managed by its own MFD model. This segmentation improves congestion control precision by capturing local traffic dynamics, while the modular structure of multiple independent MFDs actually simplifies the overall system architecture compared to a single complex city-wide model.
Solution Approach 2:
The patent employs a universal MFD modeling approach that can be applied to each sub-region independently. This multi-functionality allows the same MFD framework to handle different local conditions across multiple partitions, reducing system complexity through standardization while maintaining precision.
3Measurement precision
If real-time traffic data processing is implemented across the entire metropolitan area, then congestion identification accuracy is improved, but computational burden increases
Solution Approach 1:
The patent processes traffic data independently within each sub-region using local MFD models. This segmentation reduces computational burden by avoiding the need to process entire metropolitan area data simultaneously, while still achieving accurate congestion identification through distributed real-time processing across multiple smaller units.
Data Source
AI summary
An example operation includes one or more of receiving traffic data from a plurality of transports that are currently in operation within a predetermined geographic area, partitioning a map of the predetermined geographic area into a plurality of partitions based on link states within the traffic data, generating a plurality of macroscopic fundamental diagrams (MFDs) for the plurality of partitions based on flow rates and link densities in the traffic data, and mitigating congestion within the predetermined geographic area based on the plurality of MFDs for the plurality of partitions.