Video-Based Signal Light Priority for Urban Transit ETA Control
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Solution Overview
Problem
Existing traffic control systems face limitations in accurately determining vehicle location and estimated time of arrival (ETA) due to reliance on satellite-based positioning, which fails in urban areas with obstructions, and on-board computing systems that are inflexible and lack interoperability, leading to inefficient signal light control and prioritization, especially for mass transit vehicles.
Innovation Solution
A system using vehicle-mounted cameras to determine vehicle location and ETA through imaging unique landmarks and known objects at intersections, combined with wireless communication to adjust signal lights, allowing for real-time priority management and schedule adherence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If satellite-based positioning systems are used to determine vehicle location and ETA, then the system can provide location data for traffic control, but the system fails in urban areas with obstructions and lacks reliability
Solution Approach 1:
The patent introduces camera-based visual recognition as an intermediary method to determine vehicle location when satellite-based positioning fails. The system uses cameras mounted on vehicles to capture images of landmarks and known objects, then processes these images to calculate vehicle position and ETA, providing a reliable alternative in urban canyons where satellite signals are blocked
Solution Approach 2:
The system changes the measurement parameter from satellite signal reception to visual feature recognition. By transitioning from GPS coordinates to image-based landmark recognition, the system overcomes the limitation of signal obstruction and maintains reliable location determination in challenging urban environments
2Ease of operation
If on-board VCUs and single-vendor solutions are used for traffic control systems, then the system can provide integrated functionality, but the system lacks interoperability and flexibility
Solution Approach 1:
The patent creates a universal communication interface that allows different vendor equipment to interoperate. The system defines standardized protocols for vehicle-to-infrastructure communication, enabling VCUs from one vendor to communicate with traffic controllers from another vendor, thus achieving multi-vendor compatibility while maintaining integrated functionality
Solution Approach 2:
The system segments the traffic control functionality into independent modular components with well-defined interfaces. By separating communication protocols, data formats, and interaction standards into discrete layers, the patent enables different vendors to develop compatible components that can be assembled into a fully integrated system
3Device complexity
If traditional timers are used to control signal lights, then the system is simple to implement, but the system cannot react dynamically to traffic conditions
Solution Approach 1:
The patent implements a feedback mechanism where real-time vehicle location and ETA data from the camera system are continuously monitored and used to dynamically adjust signal light timing. The system processes visual data to determine approaching vehicles and modifies intersection signals accordingly, creating a closed-loop control system that responds to actual traffic conditions rather than following fixed schedules
Solution Approach 2:
The system transitions from static timer-based signal control to dynamic event-driven control. Signal timing is no longer predetermined but adapts in real-time based on detected vehicle positions and estimated times of arrival, allowing the traffic system to optimize flow efficiency according to actual conditions while maintaining manageable complexity through automated decision algorithms
4Loss of time
If ETA-based priority systems are implemented, then mass transit vehicles can maintain schedules, but the system requires complex on-board computing and satellite dependency
Solution Approach 1:
The patent enables the vehicle's own camera system to perform location determination and ETA calculation without relying on external satellite infrastructure or complex on-board computing. The visual recognition system processes images locally to determine vehicle position and predict arrival times, providing self-sufficient schedule adherence capability that reduces both satellite dependency and computational requirements
Data Source
AI summary
Methods and systems for modifying a traffic flow control systems wherein a vehicle's real-time location and estimated time of arrival (ETA) is utilized to modify the priority management cycles of multiple traffic lights in a traffic grid, and the vehicle's real-time location and ETA are determined, at least in part, via the use of video processing.