Stereo Vision Source Lane Detection for Drive-Through Merges
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Solution Overview
Problem
Inefficient and error-prone manual tracking of vehicle source lanes during merges in drive-through operations, leading to wasted employee time and customer frustration.
Innovation Solution
A stereo-vision system using a processor-connected optical stereo camera or camera network to determine the source lane of moving items by calculating distances and creating temporal depth profiles, with initial and confirmation signature profiles to ensure accurate transaction ordering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If employees manually track source lanes using video cameras and monitors, then lane tracking is performed, but employee effort is wasted and human error occurs
Solution Approach 1:
The system enables self-service automation where the computerized system automatically detects vehicles, determines source lanes, and manages merge ordering without human intervention. The stereo cameras and processors autonomously perform tasks previously requiring employee attention, eliminating both time loss and human error in lane tracking
Solution Approach 2:
The patent replaces the manual mechanical tracking system (employees watching monitors) with an automated optical and computational system. Stereo cameras capture images, and processors automatically analyze depth profiles to determine source lanes, substituting human cognitive and manual labor with automated vision and computation systems
2Productivity
If manual tracking is used to determine source lanes, then lane identification is achieved, but human error wastes time and creates customer frustration
Solution Approach 1:
The system implements feedback mechanisms where the processor continuously monitors vehicle positions, depth profiles, and merge sequences. The system uses confirmed source lane information to dynamically adjust and verify transaction ordering, providing feedback loops that ensure accuracy and enable corrective actions if errors are detected in real-time
Solution Approach 2:
The patent introduces computerized processing systems as intermediaries between vehicle detection and transaction management. The processor acts as a mediator that receives raw camera data, performs depth analysis to determine source lanes, and outputs verified merge sequences to transaction systems, ensuring accurate ordering without direct human intervention
3Measurement precision
If stereo cameras and temporal depth profiles are used to determine source lanes, then accuracy is improved, but device complexity increases
Solution Approach 1:
The stereo camera system and processor serve multiple functions: capturing images, calculating depth profiles, determining source lanes, tracking vehicle positions, and verifying merge sequences. This multi-functionality reduces the need for separate specialized devices, managing complexity while maintaining high measurement precision through integrated systems
Solution Approach 2:
The patent transitions from 2D camera images to 3D spatial understanding by calculating temporal depth profiles. This dimensional transformation enables precise source lane determination by adding depth information, allowing the system to distinguish vehicles in overlapping 2D projections through their different 3D positions in space and time
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
Automates the determination of vehicle source lanes, reducing human error and improving efficiency by accurately ordering transactions and confirming lane changes, thus enhancing operational speed and customer satisfaction.
Implementation Method 1
The processor calculates the distances the moving items are from the stereo camera (or distances from a reference camera, if a camera network is used) in the horizontal direction based on differences between images of the moving items obtained by the multiple cameras of the stereo cameras
Data Source
AI summary
Methods and devices acquire images using a stereo camera or camera network aimed at a first location. The first location comprises multiple parallel primary lanes merging into a reduced number of at least one secondary lane, and moving items within the primary lanes initiate transactions while in the primary lanes and complete the transactions while in the secondary lane. Such methods and devices calculate distances of the moving items from the camera to identify in which of the primary lanes each of the moving items was located before merging into the secondary lane. These methods and devices then order the transactions in a merge order corresponding to a sequence in which the moving items entered the secondary lane from the primary lanes. Also, the methods and devices output the transactions in the merge.