AR Navigation Overlays for Autonomous Vehicle Handoff Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current navigation systems for autonomous vehicles and mobile devices face challenges in accurately identifying and interacting with pickup and drop-off zones, especially in environments where GPS is unreliable, and lack effective user interfaces for seamless handovers between autonomous and human-driven modes.
Innovation Solution
The implementation of an augmented reality system that uses HD Maps, object recognition, and AI-powered mobile applications to provide precise navigation and interaction overlays on mobile devices and vehicle displays, enabling accurate identification of locations and handoff points through a combination of sensors, cameras, and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS-based navigation is used for autonomous vehicles, then the system is simple and widely compatible, but navigation accuracy deteriorates in GPS-challenged environments
Solution Approach 1:
The patent combines multiple navigation systems (GPS, HD Maps, object recognition, depth cameras, LIDAR, radar) into an integrated navigation system. This merging allows the system to maintain simplicity of individual components while achieving high navigation accuracy through their coordinated operation, resolving the contradiction between measurement precision and device complexity.
Solution Approach 2:
The patent introduces HD Maps and object recognition systems as intermediary layers between GPS and the vehicle navigation. These intermediaries enhance GPS accuracy by providing contextual information about the environment, allowing the system to achieve high precision without proportionally increasing overall system complexity.
2Ease of operation
If traditional navigation interfaces are used, then the device complexity is low, but ease of operation deteriorates during autonomous-human driving handoffs
Solution Approach 1:
The patent transitions from traditional 2D navigation interfaces to augmented reality overlays that project navigation information into the driver's field of view. This dimensional change from flat screens to spatial overlays improves ease of operation during handoffs by providing intuitive, context-aware guidance without significantly increasing interface complexity.
Solution Approach 2:
The patent uses color-coded overlays and visual indicators in the augmented reality interface to convey different navigation states and handoff instructions. These color changes provide immediate, intuitive feedback to drivers, improving ease of operation during mode transitions without requiring complex interface elements.
3Measurement precision
If basic object recognition is used, then the system complexity is low, but measurement precision deteriorates for pickup and drop-off location identification
Solution Approach 1:
The patent implements a nested recognition system where basic object recognition identifies general locations, and deeper levels of recognition (using depth cameras, LIDAR, and contextual analysis) provide precise location identification. This nested approach achieves high measurement precision while managing system complexity through hierarchical processing.
Solution Approach 2:
The patent performs preliminary object recognition and location identification using available sensors before requiring high-precision measurement. This preliminary action prepares the system in advance, allowing it to activate more complex recognition algorithms only when needed, thereby achieving high precision without continuously maintaining maximum system complexity.
Data Source
AI summary
An augmented navigational system is provided for autonomous vehicles. The augmented navigational system may further be coupled to an artificial intelligence system that provides object recognition and image recognition. A machine learning system may provide further feedback as to whether the pickup and drop off location was appropriate, and whether the recognition of one or more objects was appropriate.