AR Vehicle Identification via Sensor Data Exchange
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Solution Overview
Problem
Ride hailing services face challenges in connecting users and vehicles at the start of a trip, as users and drivers often lack identification of each other, leading to frustration, delays, and incorrect passenger pickups.
Innovation Solution
The use of sensors on user devices and vehicles to capture and exchange image data, including augmented reality elements, to facilitate identification and orientation, enabling users to confirm the correct vehicle and vehicle systems to determine the correct passenger through image recognition and sensor data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional ride hailing connection methods are used, then the system is simple to operate, but users and drivers cannot reliably identify each other, leading to frustration and delays
Solution Approach 1:
The patent introduces an intermediary identification system using image data capture devices and processing systems. These intermediaries facilitate reliable identification between users and drivers by capturing, processing, and transmitting visual identification data, resolving the contradiction between reliability and complexity through a dedicated mediation layer.
Solution Approach 2:
The patent replaces traditional mechanical or manual identification methods (such as physical meeting and verification) with electronic image capture and processing systems. This substitution enables automated, reliable identification while managing complexity through digital rather than physical interaction protocols.
2Measurement precision
If image data capture and processing systems are implemented, then identification accuracy improves, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the identification system into distinct functional modules: image capture devices, processing systems, and communication interfaces. This segmentation allows each component to be optimized independently, improving identification accuracy while managing overall system complexity through modular architecture.
Solution Approach 2:
The patent implements multi-functional processing systems that can handle various types of image data and identification scenarios. By creating universal processing capabilities that serve multiple functions (capture, process, transmit, and store identification data), the system achieves high accuracy without proportionally increasing complexity.
3Productivity
If real-time image data exchange is implemented, then connection efficiency improves, but energy consumption and data transmission requirements increase
Solution Approach 1:
The patent implements periodic or on-demand image data exchange rather than continuous real-time transmission. The system captures and transmits identification data at key moments (when users arrive, when vehicles arrive), maintaining connection efficiency while significantly reducing energy consumption compared to continuous data streams.
Data Source
AI summary
Techniques for assisting a passenger to identify a vehicle and for assisting a vehicle to identify a passenger are discussed herein. Also discussed herein are techniques for capturing data via sensors on a vehicle or user device and for presenting such data in various formats. For example, in the context of a ride hailing service using autonomous vehicles, the techniques discussed herein can be used to identify a passenger of the autonomous vehicle at the start of a trip, and can be used to assist a passenger to identify an autonomous vehicle that has been dispatched for that particular passenger. Additionally, data captured by sensors of the vehicle and/or by sensors of a user device can be used to initiate a ride, determine a pickup location, orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and/or enrich a user experience.