Autonomous Route Segment QoS for Achievable Driving Autonomy
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Solution Overview
Problem
Current autonomous vehicle systems lack the ability to dynamically assess and communicate the quality of service (QoS) for autonomous driving, which affects user experience and the feasibility of autonomous driving, especially in varying conditions such as weather and road conditions.
Innovation Solution
A system that includes a vehicle computing device capable of determining autonomous driving QoS scores for route segments based on factors like high-definition map availability, weather, road conditions, and sensor health, allowing users to select routes based on achievable autonomy levels and providing guaranteed QoS, incorporating user preferences and policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous driving systems operate without dynamic QoS assessment, then system complexity is reduced, but user experience and feasibility of autonomous driving deteriorate due to inability to adapt to varying conditions
Solution Approach 1:
The patent segments the autonomous driving system into multiple independent QoS assessment modules, each evaluating specific factors (weather, road conditions, sensor health, map availability) separately. This modular segmentation enables dynamic adaptability without creating a monolithic complex system, as each segment can be developed and maintained independently while contributing to the overall QoS determination.
Solution Approach 2:
The system performs preliminary QoS assessment before autonomous driving operations begin. By pre-evaluating multiple factors and determining the achievable autonomy level in advance, the system prepares adaptability measures without requiring complex real-time adjustments during driving, thus managing system complexity while maintaining high adaptability.
2Loss of information
If the system provides detailed QoS scores for route segments, then user experience improves through informed route selection, but information processing requirements and system complexity increase
Solution Approach 1:
The patent extracts only the essential QoS information needed for user decision-making from the comprehensive set of assessed factors. Instead of presenting all raw data about weather, road conditions, sensor health, and map availability, the system extracts and presents key QoS scores and achievable autonomy levels, reducing information processing complexity while maintaining sufficient information availability for users.
Solution Approach 2:
The system transforms multiple detailed assessment parameters (weather conditions, road surface quality, sensor operational status, map data completeness) into a simplified QoS score parameter. This parameter transformation reduces the dimensionality of information presented to users while preserving the essential quality differences between route segments.
3Reliability
If the system guarantees minimum QoS levels for route segments, then user trust and acceptability of autonomous driving increase, but the restrictiveness of route options increases
Solution Approach 1:
The patent implements dynamic QoS threshold adjustment based on user preferences and contextual factors. The minimum guaranteed QoS level is not fixed but can be adjusted dynamically, allowing the system to maintain reliability guarantees while adapting to different user needs and conditions. This dynamic approach prevents overly restrictive route limitations while ensuring adequate service quality.
Solution Approach 2:
The system changes the QoS parameter thresholds based on user profiles and specific driving contexts. By adjusting the minimum acceptable QoS levels dynamically rather than using fixed thresholds, the system maintains reliability guarantees tailored to different users while preserving route selection flexibility for varying operational conditions.
Data Source
AI summary
Technologies for autonomous vehicle driving quality of service (QoS) determination and communication include an advanced vehicle with a vehicle computing device. The computing device determines multiple route segments of one or more routes to a destination. The computing device determines, for each route segment, one or more autonomous driving factors that are each indicative of an autonomy level achievable by the advanced vehicle for the associated route segment. Factors may include map availability, weather conditions, road conditions, or other factors. The computing device determines, for each route segment, an autonomous QoS score based on the autonomous driving factors. The computing device may rank multiple routes to the destination based on the autonomous QoS scores associated with the route segments of those routes. The computing device may display a proposed route to a user of the advanced vehicle and receive a selection from the user. Other embodiments are described and claimed.