Traffic Signal Control Using Dynamic Phase Timing
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Solution Overview
Problem
Existing traffic signal systems often lead to suboptimal traffic management, causing jams and unnecessary delays for vehicles and pedestrians, especially on secondary roads, due to their inability to adapt to real-time traffic conditions and varying requirements.
Innovation Solution
A method that uses a local traffic model with a specified evaluation criterion to determine and adapt manipulated variables for signal control, allowing for efficient and flexible management of traffic flow with minimal computing power and data transfer, and includes features for reducing pollutant emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed time interval switching is used for signal phases, then the control system is simple and reliable, but it does not adapt to current traffic situations causing unnecessary delays
Solution Approach 1:
The patent implements dynamic signal phase duration adjustment by continuously monitoring traffic flow parameters and automatically modifying the timing of signal phases. The system transitions from fixed time intervals to variable time intervals based on real-time traffic conditions, allowing the control system to adapt dynamically without requiring complex infrastructure changes.
Solution Approach 2:
The system changes the temporal parameters of signal phases (duration, timing) based on detected traffic flow characteristics. By adjusting phase durations and inter-green intervals as parameters, the system achieves adaptability to varying traffic situations while maintaining a relatively simple control architecture.
2Adaptability or versatility
If complex adaptive control systems are implemented, then traffic control can adapt to varying requirements, but computing power and data transfer requirements increase
Solution Approach 1:
The control system is segmented into modular functional units: detection modules for specific traffic parameters, evaluation modules for assessing traffic situations, and control modules for adjusting signal phases. This segmentation allows the system to implement adaptive control strategies while distributing computational loads efficiently and reducing overall energy consumption.
Solution Approach 2:
The system implements partial adaptive control by focusing on the most critical traffic parameters and phases rather than attempting to optimize all aspects simultaneously. This selective approach achieves sufficient adaptability for improving traffic flow while minimizing computing power requirements and energy consumption.
3Loss of time
If fixed signal timing is used, then the system is easy to operate and maintain, but vehicles on secondary roads wait unnecessarily long times
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor traffic flow on both primary and secondary roads. Based on this feedback, the control system dynamically adjusts signal phase timing to reduce wait times for vehicles on secondary roads during periods of low traffic, while maintaining simple operation through automated adjustments without requiring manual intervention.
Data Source
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AI summary
In a method for controlling a traffic signal system (1) at an intersection, in order to easily integrate it into an existing system, to keep the required computing power and data transfer low, and to ensure a reduction in pollutant emissions in the area of the intersection, it is proposed that: - at least one input parameter (10) is passed to a traffic control device (2), - the traffic control device (2) determines initial traffic parameters (31) of the current traffic situation, - at least one evaluation criterion (4) is specified, - the initial traffic parameters (31) and the at least one evaluation criterion (4) are passed to an evaluation device (6), - the evaluation device (6) determines control variables (7) that depend on the traffic parameters and the evaluation criterion, and the traffic signal system (1) is operated with the control variables (7).