Vehicle Authentication Using Image and Weight Data
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Solution Overview
Problem
Vehicle-sharing and ride-hailing fleets lack effective driver authentication and personalization systems, leading to insufficient security and user experience.
Innovation Solution
A method and system using a processor to authenticate drivers by obtaining image data from cameras and weight data from pressure sensors, matching it with vehicle-sharing account information, and enabling vehicle activation only if the driver is verified as valid and compliant with account settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods are used, then device complexity is reduced, but driver authentication reliability is insufficient
Solution Approach 1:
The authentication system is divided into multiple independent modules: image capture module, weight detection module, facial recognition module, and verification module. Each module performs a specific function, and their results are combined to achieve comprehensive authentication, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The system introduces an intermediary processing layer that coordinates between sensors (cameras, pressure sensors) and the authentication decision logic. This intermediary layer manages the complex interactions between multiple authentication factors while presenting a unified interface, thereby improving reliability without proportionally increasing overall system complexity.
2Reliability
If multiple authentication factors are implemented, then driver authentication reliability is improved, but ease of operation deteriorates
Solution Approach 1:
User profile information including expected weight range and facial features is pre-configured in the system during account creation. When a user approaches the vehicle, the system automatically retrieves these pre-set parameters and compares them with real-time sensor data, eliminating the need for manual input and maintaining ease of operation while ensuring reliable multi-factor authentication.
Solution Approach 2:
The system performs self-verification by automatically comparing captured image data and weight measurements against stored profile information. The authentication process occurs without user intervention beyond natural actions (sitting in the driver's seat), as the system autonomously validates multiple factors and activates the vehicle accordingly.
3Adaptability or versatility
If personalization features are added, then user experience is improved, but device complexity increases
Solution Approach 1:
The authentication system serves multiple functions: it verifies driver identity, checks compliance with operating restrictions, and enables personalization of vehicle settings. By using the same image and weight data for both security verification and preference customization, the system achieves adaptability without proportionally increasing complexity.
Solution Approach 2:
User preferences and vehicle configuration settings are pre-associated with each user account in the database. Upon successful authentication, the system automatically retrieves and applies the corresponding personalized settings (seats, mirrors, climate control), eliminating the need for complex real-time configuration interfaces and simplifying the user experience.
Data Source
AI summary
A method and system are disclosed and include, in response to a user being located within a vehicle associated with the vehicle-sharing request, obtaining, using a processor configured to execute instructions stored in a nontransitory computer-readable medium, image data corresponding to the user from a camera. The method also includes determining, using the processor, whether the image data corresponds to an image associated with a vehicle-sharing account of the user. The method also includes in response to determining the image data corresponds to the image, enabling, using the processor, the user to activate the vehicle.