Self-Configuring Traffic Signal Controller Using Trajectory Sensors
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Solution Overview
Problem
Current traffic detection systems, such as inductive loop systems, are expensive to install and maintain, and traditional traffic controllers lack the ability to utilize geometric information and real-time vehicle trajectory data for optimized signal timing, leading to inefficient and costly manual adjustments.
Innovation Solution
A self-configuring traffic signal controller system that uses trajectory sensors like radar, video cameras, or hybrid systems to collect vehicle trajectory data, transforming it into coordinate-based information, and computes factors like delay, stop, capacity, and safety to adjust signal timing dynamically, incorporating user-defined weights and policies for optimized signal control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inductive loop systems are used for traffic detection, then vehicle presence can be detected, but installation and maintenance costs increase due to road work requirements
Solution Approach 1:
The patent replaces mechanical inductive loop sensors embedded in pavement with optical/radar-based trajectory sensors mounted on poles or luminaires. This substitution eliminates the need for road work, lane closures, and pavement drilling, thereby reducing installation and maintenance costs while maintaining traffic detection capability.
Solution Approach 2:
The patent introduces trajectory sensors as an intermediary device that detects vehicle presence and characteristics from above the roadway rather than from within the pavement. This intermediary approach allows traffic monitoring without direct contact with the road surface, avoiding the need for road work and associated costs.
2Productivity
If traditional traffic controllers are used, then signal timing can be controlled, but they lack the ability to utilize geometric information and real-time trajectory data for optimized timing
Solution Approach 1:
The patent implements a feedback mechanism where trajectory sensors continuously provide real-time vehicle position, speed, and acceleration data to the traffic controller. The controller processes this data along with geometric information to dynamically adjust signal timing, creating a closed-loop system that optimizes traffic flow based on current conditions rather than relying on fixed or manually adjusted timing.
Solution Approach 2:
The patent transforms static, manually-configured signal timing into a dynamic system that automatically adapts to changing traffic conditions. By utilizing real-time trajectory data and geometric information, the controller continuously optimizes signal timing parameters, enabling the system to respond flexibly to varying traffic patterns throughout the day.
3Adaptability or versatility
If manual adjustments are used for signal timing, then configuration can be performed, but it is expensive and time-consuming
Solution Approach 1:
The patent enables the traffic controller to automatically configure and optimize its own signal timing parameters using embedded processing capabilities. The system self-adjusts timing parameters based on real-time trajectory data and geometric information without requiring external manual intervention, thereby reducing both time and cost while maintaining adaptability to changing conditions.
Solution Approach 2:
The patent incorporates geometric information about the intersection into the controller's memory in advance, preparing the system for rapid real-time optimization. By having geometric data pre-loaded and processed algorithms ready, the system can immediately begin optimizing signal timing when deployed, eliminating the need for time-consuming manual configuration and adjustments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides more accurate and efficient signal timing adjustments than traditional methods, reducing costs and improving traffic flow by utilizing real-time vehicle trajectory data and geometric awareness, enabling automated reconfiguration based on user-defined objectives.
Implementation Method 1
a radar, a video camera, or a hybrid radar and video camera
Data Source
AI summary
Embodiments describe new mechanisms for signalized intersection control. Embodiments expand inputs beyond traditional traffic control methods to include awareness of agency policies for signalized control, industry standardized calculations for traffic control parameters, geometric awareness of the roadway and/or intersection, and/or input of vehicle trajectory data relative to this intersection geometry. In certain embodiments, these new inputs facilitate a real-time, future-state trajectory modeling of the phase timing and sequencing options for signalized intersection control. Phase selection and timing can be improved or otherwise optimized based upon modeling the signal's future state impact on arriving vehicle trajectories. This improvement or optimization can be performed to reduce or minimize the cost basis of a user definable objective function.