Vehicle Occupant Notification for Autonomous Driving Efficiency
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Solution Overview
Problem
Autonomous driving assistance systems do not consistently inform users of their operating efficiencies and the factors affecting these efficiencies, leading to user uncertainty and loss of confidence when systems malfunction or operate suboptimally.
Innovation Solution
A computing device in the vehicle processes sensor data to derive a data quality parameter, compares it to established reference ranges, and generates notifications to users about system efficiency, providing reasons for efficiency drops when thresholds are reached or sustained.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous driving assistance systems operate without continuous user notification, then system simplicity is maintained, but user confidence and awareness of system efficiency deteriorate
Solution Approach 1:
The system continuously monitors sensor data quality parameters and provides feedback to the user through notifications when efficiency drops below thresholds. This feedback loop maintains user confidence by keeping them informed about system performance without requiring complex additional hardware, as it leverages existing sensor data processing capabilities.
Solution Approach 2:
The patent introduces an intermediary notification system that mediates between the autonomous driving system and the user. This intermediary layer processes sensor data quality parameters and translates them into user-friendly notifications, maintaining system reliability while avoiding direct complex interactions between the autonomous system and user awareness.
2Loss of information
If the system provides detailed notifications about efficiency drops, then user awareness and confidence improve, but information processing requirements and notification complexity increase
Solution Approach 1:
The notification system applies local quality by providing different levels of information based on the specific efficiency drop scenario. Rather than notifying about all parameter changes uniformly, it selectively notifies users about significant efficiency drops below defined thresholds, focusing information delivery where it matters most while reducing overall notification complexity.
Solution Approach 2:
The system uses parameter changes in sensor data quality as triggers for notifications. By monitoring changes in data quality parameters against reference thresholds, the system efficiently determines when user notification is necessary, balancing comprehensive information provision with manageable notification complexity through parameter-based decision making.
3Measurement precision
If continuous monitoring of sensor data quality is implemented, then system operating efficiency awareness improves, but computational load and energy consumption increase
Solution Approach 1:
The system implements partial monitoring by continuously tracking sensor data quality parameters but only generating notifications when efficiency drops below specific thresholds. This partial action approach maintains precise efficiency measurement capability while reducing energy consumption by avoiding continuous notification generation and user interaction for every parameter fluctuation.
Solution Approach 2:
The patent establishes reference thresholds for data quality parameters in advance through preliminary calibration or predefined standards. This preliminary action allows the continuous monitoring system to efficiently compare real-time sensor data against pre-established benchmarks, reducing computational load during operation while maintaining precise efficiency measurement and awareness.
Data Source
AI summary
A computing device for a vehicle is provided. The computing device includes one or more processors for controlling operation of the computing device, and a memory for storing data and program instructions usable by the one or more processors, wherein the one or more processors are configured to execute instructions stored in the memory to receive sensor data relating to operation of an autonomous driving assistance system, process the received sensor data to derive a value for an assistance system data quality parameter, compare the quality parameter value to a reference, and generate a notification including a result of the comparison.