Dynamic Traffic Control System Using Real-Time Object Weights
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Solution Overview
Problem
Current traffic control systems are inefficient due to reliance on outdated information, failing to effectively manage the complex interactions between various traffic objects, such as vehicles and pedestrians, leading to increased congestion and poor traffic flow.
Innovation Solution
Implementing a dynamic traffic control system that utilizes real-time data from GPS and online sources to assign weights to traffic objects based on their characteristics and environmental conditions, allowing for optimized routing and priority management at intersections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traffic control signals work based on historical records, then the control system is simple to implement, but the traffic control efficiency deteriorates due to outdated information
Solution Approach 1:
The patent transforms static historical-based traffic control into a dynamic real-time system. Traffic object weights are dynamically calculated based on current environmental conditions, object characteristics, and real-time traffic data, allowing the control system to adapt continuously changing traffic scenarios rather than relying on fixed historical patterns
Solution Approach 2:
The system implements feedback mechanisms by continuously collecting real-time traffic data from multiple sources (GPS, sensors, online information) and using this feedback to adjust traffic object weights and control signal decisions. This closed-loop feedback enables the system to respond to actual current conditions rather than relying on outdated historical records
2Productivity
If real-time traffic information is collected and processed, then traffic control efficiency is improved, but the system complexity increases
Solution Approach 1:
The patent introduces a traffic server as an intermediary component that centralizes the complex tasks of collecting, processing, and analyzing real-time traffic data from multiple sources. This intermediary architecture manages system complexity by consolidating data processing functions while maintaining simple interfaces with traffic control signals and data sources
Solution Approach 2:
The system segments the traffic control problem into manageable components: traffic object identification, characteristic extraction, weight calculation based on multiple criteria, and signal control decisions. This segmentation allows each component to be processed independently and systematically, making the overall complex system more manageable and implementable
3Measurement precision
If traffic objects are dynamically weighted based on multiple criteria, then the prioritization accuracy is improved, but the calculation complexity increases
Solution Approach 1:
The patent changes the parameter representation from simple categorical traffic object types to continuous weight values calculated from multiple criteria parameters. Each traffic object's priority is represented by a weighted sum of multiple factors (object characteristics, environmental conditions, traffic flow), allowing nuanced prioritization while using standardized calculation formulas to manage complexity
Data Source
AI summary
Traffic flow control. A method identifies traffic in an area. The traffic includes traffic objects. The identifying obtains identifiers of traffic objects in the area. Each traffic object is identified by a respective identifier of the traffic object identifiers. The method also dynamically assigns weights to the traffic objects based on pre-established traffic criteria. Each traffic object is assigned a respective weight of the dynamically assigned weights. The pre-established traffic criteria each include at least one weight value. The weight assigned to a traffic object is based on the weight values of a set of traffic criteria, of the pre-established traffic criteria, applicable to the traffic object and reflects a level of prioritization of a right-of-way of the traffic object. The method also controls flow of the traffic in the area. The controlling the flow includes controlling at least one traffic control signal based on the dynamically assigned weights.