In-Vehicle Digital Scout Attention Guidance System
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Solution Overview
Problem
In increasingly self-driving vehicles, occupants may miss points of interest along the travel route due to their limited spatial range of attention, as they pay less attention to the surrounding area, leading to a need for an assistance system that can guide their attention based on individual interests.
Innovation Solution
A vehicle assistance system, known as the 'In-Vehicle Digital Scout,' uses an outside camera to generate a video stream, a control unit to analyze and mark entities of interest, and a human machine interface to acquire and store occupant statements, forming an interest profile and providing augmented reality displays to guide attention to relevant entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If self-driving functionality is implemented to relieve driver pressure, then driver workload is reduced, but driver attention to surrounding area and points of interest decreases
Solution Approach 1:
The patent introduces an intermediary system (attention guidance system with display unit and marker generation) that mediates between the self-driving functionality and the driver's need to notice points of interest. The system automatically detects points of interest and presents them to the driver through markers, eliminating the need for the driver to actively scan the environment while ensuring important information is not missed.
Solution Approach 2:
The system enables the vehicle's own systems (sensors, processors) to perform the function of detecting and identifying points of interest that would otherwise require the driver's attention. The vehicle essentially serves itself by autonomously monitoring the environment and selectively presenting relevant information to the driver, freeing the driver from active surveillance while maintaining awareness.
2Ease of operation
If automated vehicle systems are used to monitor surrounding area, then driver attention is freed, but the system must process and prioritize information to guide attention effectively
Solution Approach 1:
The system extracts only the most relevant information from the complex sensor data stream by using predefined criteria and machine learning models to identify points of interest. Instead of presenting all detected objects, the system selectively extracts and presents only those elements that match interest profiles or represent significant events, simplifying the information load on the driver.
Solution Approach 2:
The system dynamically changes parameters such as marker visibility, priority levels, and attention thresholds based on driving conditions, vehicle speed, and detected occupant interest profiles. This adaptive parameter adjustment allows the system to manage information complexity by presenting more detailed markers when conditions permit and fewer, more critical markers when conditions demand minimal distraction.
Data Source
AI summary
A vehicle assistance system with at least one outside camera, a control unit, at least one display unit, an occupant identification unit, and a human machine interface (Human Machine Interface, HMI).