Distributed Tram Traffic Control Using Local Evaluation
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Solution Overview
Problem
Existing traffic control methods often result in suboptimal solutions for varying traffic situations, leading to unnecessary waiting times for vehicles and pedestrians, particularly on side streets, and increased pollutant emissions, due to inefficient coordination of signal systems at intersections.
Innovation Solution
A method that uses a local traffic model with a simple evaluation criterion to determine and adapt signal control strategies, allowing for quick changes in response to current traffic conditions, reducing computing power and data transfer requirements, and integrating easily into existing systems, while ensuring reduced pollutant emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If complex centralized traffic control systems are used to optimize traffic flow, then traffic management capability is improved, but computing power requirements and data transfer requirements increase significantly
Solution Approach 1:
The patent divides the centralized traffic control system into distributed local control units at each intersection. Each unit independently processes local traffic data and makes signaling decisions, eliminating the need for a single powerful central computer. This segmentation reduces overall computing power requirements while maintaining traffic optimization capabilities.
Solution Approach 2:
The patent implements local traffic modeling and evaluation at each intersection rather than centralized processing. Each control unit uses simple local traffic models to evaluate current conditions and determine optimal signal configurations, reducing data transfer requirements and computing power consumption while achieving effective traffic flow optimization.
2Device complexity
If fixed time interval signal switching is used, then system simplicity is maintained, but waiting times for vehicles and pedestrians increase unnecessarily
Solution Approach 1:
The patent transitions from fixed time interval signal switching to dynamic signal control based on real-time traffic conditions. Local control units continuously evaluate current traffic situations using simple local models and adjust signal configurations dynamically, reducing waiting times while maintaining system simplicity through rule-based decision logic.
Solution Approach 2:
The patent implements feedback mechanisms where local control units continuously monitor traffic conditions and adjust signal configurations based on observed traffic patterns and performance metrics. This feedback-driven approach optimizes waiting times by adapting to actual traffic demand rather than following predetermined fixed schedules.
3Use of energy by moving object
If simple local traffic models are used, then computing power and data transfer requirements are reduced, but ability to handle varying traffic situations decreases
Solution Approach 1:
The patent enables each local control unit to autonomously handle varying traffic situations using simple local traffic models and predefined evaluation criteria. The distributed architecture allows each unit to independently adapt to local conditions without requiring complex centralized processing, achieving both low computing power consumption and high adaptability to varying traffic scenarios.
Data Source
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AI summary
In a method for traffic control of a road section with several intersections, wherein at least two of the intersections are assigned signal systems (1), it is proposed that, in order to be easily integrated into an existing method, the required computing power and data transfer can be kept low, and a reduction of pollutant emissions in the area of the intersection can be ensured, 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), and - the signal systems (1) are operated with the control variables (7).