Drive-Thru Camera System for PEV and Pedestrian Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional drive-thru systems often exclude customers using personal electric vehicles (PEVs) and pedestrians due to safety policies, leading to revenue loss for restaurants, especially during the pandemic when walk-in services were closed and drive-thru lanes did not accommodate non-car customers.
Innovation Solution
A system that uses cameras to capture images of vehicles and customers in drive-thru lanes, processing them with machine-learning models to identify the type of vehicle and customer, providing written descriptions integrated into the order workflow to ensure correct order fulfillment and lane guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If drive-through lanes use traditional metal sensors to detect vehicles, then car customers can be served, but PEV and pedestrian customers are not detected and excluded
Solution Approach 1:
The patent replaces traditional metal sensors with a camera-based computer vision system that uses image processing and machine learning to detect and classify different types of customers (cars, PEVs, pedestrians). This substitution allows the system to detect non-metallic objects and diverse customer types that metal sensors cannot detect, thereby improving adaptability while maintaining detection reliability through advanced image analysis algorithms.
Solution Approach 2:
The system changes the detection parameters from metal-specific sensor responses to multi-parameter image analysis including object shape, size, color, and spatial position. By analyzing multiple visual parameters simultaneously, the system can accurately distinguish between different customer types (cars vs. PEVs vs. pedestrians) and provide reliable detection across diverse scenarios.
2Reliability
If drive-throughs prohibit walk-up customers for safety reasons, then safety is improved, but revenue is lost from PEV and pedestrian customers
Solution Approach 1:
The system implements feedback by using captured images to verify customer identity and vehicle type, then providing this information back to staff for order fulfillment. This allows the restaurant to safely accommodate walk-up and PEV customers at the drive-through while maintaining safety protocols through visual verification, thereby converting previously excluded customers into revenue-generating patrons.
Solution Approach 2:
The computer vision system enables self-service functionality by automatically detecting customers, identifying their vehicle type, and providing written descriptions for order verification. This automated process allows PEV and pedestrian customers to place and receive orders independently without requiring staff intervention for identification, making the service both safe and revenue-generating.
3Adaptability or versatility
If separate drive-through lanes are created for cars and PEVs/walkups, then customer accommodation is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal camera-based detection system that serves multiple functions: detecting cars, PEVs, and pedestrians; determining customer type; providing lane guidance; and generating written descriptions for order verification. This single multi-functional system replaces what would otherwise require separate specialized systems for each customer type, reducing overall complexity while maintaining high adaptability across different lane configurations.
Data Source
AI summary
Cameras capture images of vehicles and customers in drive-through lanes of a store. The images are processed to identify a type of vehicle, if any, and determine whether a given customer is in a proper lane associated with cars or a proper lane associated with walkups or non cars. Customers in improper lanes are instructed to move to the proper lane to place an order. The images are further processed to generate a written description of the vehicle, if any, and a written description of the customer. The written description is linked to the customer's order and is accessible to store staff for verification when collecting payment for the order and when providing the ordered items to the customer.