Distributed Agent-Based Traffic Signal Coordination
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Solution Overview
Problem
Existing traffic signal timing systems are inefficient in highly dynamic conditions and lack coordination between intersection controllers, leading to sub-optimal solutions at the traffic system level, as they are typically centralized and only allow limited interaction between neighboring intersections.
Innovation Solution
A collaborative distributed agent-based traffic light system that uses software agents on dedicated intersection controllers to optimize signal timing phases considering feedback from all affected controllers, and incorporates network input from handheld devices to adapt to emerging situations, including emergency scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If centralized traffic signal timing systems are used, then system control and coordination are simplified, but the system becomes inefficient in highly dynamic conditions and lacks adaptability
Solution Approach 1:
The patent divides the centralized traffic signal system into distributed autonomous agents at each intersection. Each agent independently manages its own signal timing based on local traffic conditions, eliminating the need for complex centralized control while maintaining adaptability to dynamic conditions through local decision-making capabilities.
Solution Approach 2:
The system implements feedback mechanisms where agents continuously monitor local traffic conditions and adjust their signal timing in real-time. This feedback loop enables each agent to adapt to changing conditions autonomously, improving system adaptability without requiring complex centralized coordination.
2Productivity
If limited interaction between neighboring intersections is allowed, then device complexity is reduced, but coordination efficiency and system-wide optimization are compromised
Solution Approach 1:
The patent merges the decision-making capabilities of multiple intersections into a coordinated network of agents. Each agent maintains autonomy but interacts with neighboring agents to optimize system-wide performance, combining local independence with regional coordination to achieve both efficiency and manageable complexity.
Solution Approach 2:
The system dynamically adjusts the level of interaction between agents based on traffic conditions. During normal conditions, agents operate independently with minimal communication. During congestion or emergency events, agents increase interaction to coordinate response, providing adaptive coordination efficiency without requiring constant complex communication.
3Adaptability or versatility
If pre-timed signals are used, then system simplicity is maintained, but the system cannot respond to real-time traffic volume changes
Solution Approach 1:
Each traffic signal agent is equipped with autonomous decision-making capabilities that enable it to self-adjust timing based on real-time traffic detection. The agents independently monitor traffic volumes and modify their operations without external intervention, achieving real-time adaptability while maintaining operational simplicity through automated local control.
Data Source
AI summary
In this disclosure, collaborative multi-agent-based TST is presented with dedicated intersection controllers that include software agents which read local and remote detection systems and then collaboratively optimize signal timing phases by considering the feedback of all controller agents that may be affected by a change. The disclosure also presents an augmented system which considers network input from handheld remote devices to update certain traffic light phase information and adapt to emerging emergency situations.