Decentralized Traffic Signal Control for Adaptive Urban Networks
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Solution Overview
Problem
Urban traffic congestion is exacerbated by poorly timed traffic signals that fail to respond to real-time traffic patterns, leading to inefficiencies and increased congestion, particularly in networks with multiple competing flows and densely spaced intersections.
Innovation Solution
A decentralized urban traffic control system, SURTRAC, where each intersection independently and asynchronously solves a single-machine scheduling problem to allocate green time, communicating planned outflows to neighbors for coordinated behavior and achieving real-time responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized approaches are used to adjust traffic signal timings, then coordination between intersections is improved, but real-time responsiveness to locally changing traffic patterns deteriorates
Solution Approach 1:
The patent divides the traffic signal control system into autonomous agents at each intersection that independently make control decisions. Each agent segments the network control problem into local scheduling problems, allowing real-time responsiveness while maintaining coordination through information exchange about planned outflows between neighboring intersections.
2Device complexity
If pre-programmed timing plans are used, then system complexity is reduced, but adaptability to current traffic conditions deteriorates
Solution Approach 1:
The patent implements dynamic traffic signal control where each intersection agent continuously adjusts phase durations and sequences based on real-time traffic detector inputs. The system transitions from static pre-programmed plans to dynamic adaptive control that responds to changing traffic conditions while maintaining manageable complexity through localized decision-making.
3Productivity
If longer green phases are allocated to dominant traffic flow, then throughput is improved, but fairness to other movements deteriorates
Solution Approach 1:
The patent employs feedback mechanisms where traffic detectors continuously monitor queue lengths and vehicle flows for all movements at each intersection. This feedback information is used by the autonomous agent to dynamically adjust green phase allocations, ensuring that dominant flows receive adequate green time for throughput while maintaining minimum service levels for other movements, thus balancing productivity and fairness.
Data Source
AI summary
Scalable urban traffic control system has been developed to address current challenges and offers a new approach to real-time, adaptive control of traffic signal networks. The methods and system described herein exploit a novel conceptualization of the signal network control problem as a decentralized process, where each intersection in the network independently and asynchronously solves a single-machine scheduling problem in a rolling horizon fashion to allocate green time to its local traffic, and intersections communicate planned outflows to their downstream neighbors to increase visibility of future incoming traffic and achieve coordinated behavior. The novel formulation of the intersection control problem as a single-machine scheduling problem abstracts flows of vehicles into clusters, which enables orders-of-magnitude speedup over previous time-based formulations and is what allows truly real-time (second-by-second) response to changing conditions.